diff --git a/articles/examples.html b/articles/examples.html index c671828..4bb6868 100644 --- a/articles/examples.html +++ b/articles/examples.html @@ -90,7 +90,7 @@

Introduction

Kamil Slowikowski

-

2024-05-15

+

2024-06-05

hlabud is an R package that provides functions to facilitate download and analysis of human leukocyte antigen (HLA) genotype sequence alignments from IMGTHLA in R.

@@ -101,17 +101,19 @@

Introductionlibrary(hlabud) a <- hla_alignments("DRB1") a$release -#> [1] "3.56.0" -dosage(a$onehot, c("DRB1*03:01:05", "DRB1*03:02:03")) +#> [1] "3.56.0" +
+dosage(a$onehot, c("DRB1*03:01:05", "DRB1*03:02:03"))
 #>               F26 Y26 D28 E28 F47 Y47 G86 V86
 #> DRB1*03:01:05   0   1   1   0   1   0   0   1
 #> DRB1*03:02:03   1   0   0   1   0   1   1   0

What nucleotides are different?

-
+
 n <- hla_alignments("DRB1", type = "nuc")
 n$release
-#> [1] "3.56.0"
-dosage(n$onehot, c("DRB1*03:01:05", "DRB1*03:02:03"))
+#> [1] "3.56.0"

+
+dosage(n$onehot, c("DRB1*03:01:05", "DRB1*03:02:03"))
 #>               A164 T164 C171 G171 A227 T227 A240 G240 G344 T344 G345 T345 A357
 #> DRB1*03:01:05    1    0    1    0    0    1    1    0    0    1    1    0    1
 #> DRB1*03:02:03    0    1    0    1    1    0    0    1    1    0    0    1    0
@@ -123,7 +125,7 @@ 
IntroductionInstallation
 

 
The quickest way to get hlabud is to install from GitHub:

-
+
 # install.packages("devtools")
 devtools::install_github("slowkow/hlabud")

 
Below, I included a few usage examples. I hope they inspire you to
@@ -138,12 +140,12 @@ 
Get a one-hot enc
 
We can use hla_alignments("DRB1") to load the
 DRB1_prot.txt file from the latest IMGTHLA
 release:

-
+
 library(hlabud)
 a <- hla_alignments(gene = "DRB1", verbose = TRUE)
 #> Reading /home/runner/.local/share/hlabud/3.56.0/alignments/DRB1_prot.txt

 
The a object is a list with three items:

-
+
 str(a)
 #> List of 7
 #>  $ sequences: Named chr [1:3671] "MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGTERVR.LLERCIYNQEE.SVRFDSDVGEYRAVTELGRPDAEYWNSQKDLLEQRRAAVDTYCR"| __truncated__ "------------------------------------------------------.-----------.--------------------------------------------"| __truncated__ "------------------------------------------------------.-----------.--------------------------------------------"| __truncated__ "------------------------------------------------------.-----------.--------------------------------------------"| __truncated__ ...
@@ -162,7 +164,7 @@ 
Get a one-hot enc
 #>  $ file     : chr "/home/runner/.local/share/hlabud/3.56.0/alignments/DRB1_prot.txt"

 
a$sequences has amino acid sequence alignments in a
 named character vector:

-
+
 substr(head(a$sequences, 6), 1, 50)
 #>                                     DRB1*01:01:01:01 
 #> "MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGT" 
@@ -200,7 +202,7 @@ 
Get a one-hot enc
 
 
a$alleles has a matrix of amino acids with one column
 for each position:

-
+
 a$alleles[1:5,1:40]
 #>                  n29 n28 n27 n26 n25 n24 n23 n22 n21 n20 n19 n18 n17 n16 n15
 #> DRB1*01:01:01:01 "M" "V" "C" "L" "K" "L" "P" "G" "G" "S" "C" "M" "T" "A" "L"
@@ -222,7 +224,7 @@ 
Get a one-hot enc
 #> DRB1*01:01:01:05 "D" "T" "R" "P" "R" "F" "L" "W" "Q" "L"

 
a$onehot has a one-hot encoded matrix with one column
 for each amino acid at each position:

-
+
 a$onehot[1:5,1:25]
 #>                  n29unk Mn29 n28unk Ln28 Vn28 n27unk Cn27 n26unk Ln26 n25unk
 #> DRB1*01:01:01:01      0    1      0    0    1      0    1      0    1      0
@@ -244,7 +246,7 @@ 
Get a one-hot enc
 #> DRB1*01:01:01:05    1      0    1      0

 
What is a one-hot encoded matrix? Here is a simple example to
 demonstrate the idea:

-
+
 dat <- data.frame(
   V1 = c("A", "A", "B"),
   V2 = c("B", "B", "B"),
@@ -255,8 +257,9 @@ 
Get a one-hot enc
 #>   V1 V2 V3
 #> 1  A  B  C
 #> 2  A  B  B
-#> 3  B  B  B
-predict(onehot::onehot(dat), dat)
+#> 3  B  B  B

+
+predict(onehot::onehot(dat), dat)
 #>      V1=A V1=B V2=B V3=B V3=C
 #> [1,]    1    0    1    0    1
 #> [2,]    1    0    1    1    0
@@ -266,7 +269,7 @@ 
Get a one-hot enc
 
Convert genotypes to a dosage matrix
 

 
Suppose we have some individuals with the following genotypes:

-
+
 genotypes <- c(
   "DRB1*12:02:02:03,DRB1*12:02:02:03",
   "DRB1*04:174,DRB1*15:152",
@@ -279,7 +282,7 @@ 
Convert genotypes to a dosage matr
 (e.g., 0, 1, 2).

 
We can use dosage() to convert each individual’s
 genotypes to amino acid dosages:

-
+
 dosage <- dosage(a$onehot, genotypes)
 dosage[,1:8]
 #>                                   n29unk Mn29 n28unk Vn28 n27unk Cn27 n26unk
@@ -293,8 +296,9 @@ 
Convert genotypes to a dosage matr
 #> DRB1*04:174,DRB1*15:152              0
 #> DRB1*04:56:02,DRB1*15:01:48          0
 #> DRB1*14:172,DRB1*04:160              0
-#> DRB1*04:359,DRB1*04:284:02           0
-dim(dosage)
+#> DRB1*04:359,DRB1*04:284:02           0

+
+dim(dosage)
 #> [1]   5 428

 
Note:

 
-
+
 af <- hla_frequencies()
 af
 #> # A tibble: 123,502 × 7
@@ -448,7 +452,7 @@ 
Get
 
We can use this data to plot the frequency of a specific allele
 (e.g. DQB1*02:01) in populations with more than 1000 sampled
 individuals:

-
+
 my_allele <- "DQB1*02:01"
 my_af <- af %>% filter(allele == my_allele) %>%
   filter(n > 1000) %>%
@@ -484,7 +488,7 @@ 
Compute HLA di
 
The amino acid distance matrix by Granthan 1974 (https://doi.org/10.1126/science.185.4154.862) encodes
 information about the composition, polarity, and molecular volume of
 each amino acid.

-
+
 grantham
 #>    amino    c    p     v
 #> 1    Ser 1.42  9.2  32.0
@@ -509,14 +513,14 @@ 
Compute HLA di
 #> 20   Trp 0.13  5.4 170.0

 
We can use that matrix to compute an HLA divergence metric for a set
 of individuals like this:

-
+
 my_genos <- c("A*23:01:12,A*24:550", "A*25:12N,A*11:27", "A*24:381,A*33:85")
 
 hla_divergence(my_genos)
 #> A*23:01:12,A*24:550    A*25:12N,A*11:27    A*24:381,A*33:85 
 #>           0.5131579           3.4736842           5.1078947

 
The divergence for a homozygote is equal to zero, by definition:

-
+
 hla_divergence("A*01:01,A*01:01")
 #> A*01:01,A*01:01 
 #>               0

@@ -524,7 +528,7 @@ 
Compute HLA di
 translated from the original Perl code by Pierini & Lenz 2018 (https://doi.org/10.1093/molbev/msy116).

 
The amino acid distance matrix is easily accessible, and we provide
 two built-in options “grantham” and “uniform”:

-
+
 amino_distance_matrix(method = "grantham")
 #>     A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y
 #> A   0 112 111 126 195  91 107  60  86  94  96 106  84 113  27  99  58 148 112
@@ -584,7 +588,7 @@ 
Download a
 
Here are a few examples of how to download releases or get a list of
 release names.

 
Download the latest release (default) or a specific release:

-
+
 # Download all of the data (120MB) for the latest IMGTHLA release
 install_hla(release = "latest")
 
@@ -592,7 +596,7 @@ 
Download a
 install_hla(release = "3.51.0")

 
Optionally, get or set the directory hlabud uses to store the
 data:

-
+
 getOption("hlabud_dir")
 #> [1] "/home/username/.local/share/hlabud"
 
@@ -613,7 +617,7 @@ 
Download a
 
Count the number of alleles in each IMGTHLA release
 

 
We can get a list of the release names:

-
+
 releases <- hla_releases()
 releases
 #>  [1] "3.56.0"   "3.55.0"   "3.54.0"   "3.53.0"   "3.52.0"   "3.51.0"  
@@ -622,7 +626,7 @@ 
Count the number of
 #> [19] "3.42.0"   "3.41.2"   "3.41.0"   "3.40.0"   "3.39.0"   "3.38.0"  
 #> [25] "3.37.0"   "3.36.0"   "3.35.0"   "3.34.0"   "3.33.0"   "3.32.0"

 
Then we can get the allele names for each release:

-
+
 my_alleles <- rbindlist(lapply(releases, function(release) {
   retval <- hla_alleles(release = release)
   retval$release <- release
@@ -639,7 +643,7 @@ 
Count the number of
 #> Warning in hla_alleles(release = release): unrecognized release name
 #> 'Allelelist.3412.txt'

 
Next, count how many alleles we have in each release:

-
+
 d <- my_alleles %>% count(release) %>% filter(n > 1)
 d
 #>     release     n
@@ -671,7 +675,7 @@ 
Count the number of
 #> 25:  3.56.0 39886
 #>     release     n

 
And plot the number of alleles as a line plot:

-
+
 ggplot(d) +
   aes(x = release, y = n, group = 1) +
   geom_line() +
@@ -683,7 +687,7 @@ 
Count the number of
     axis.ticks.x = element_blank(),
   )

 

-
+
 d2 <- my_alleles %>% mutate(gene = str_split_fixed(Allele, "\\*", 2)[,1]) %>% count(release, gene)
 ggplot() +
   aes(x = release, y = n) +
diff --git a/articles/examples_files/figure-html/umap-2digit-1.png b/articles/examples_files/figure-html/umap-2digit-1.png
index 09fc57f..bdafc21 100644
Binary files a/articles/examples_files/figure-html/umap-2digit-1.png and b/articles/examples_files/figure-html/umap-2digit-1.png differ
diff --git a/articles/examples_files/figure-html/umap-57-1.png b/articles/examples_files/figure-html/umap-57-1.png
index 3160652..edbc699 100644
Binary files a/articles/examples_files/figure-html/umap-57-1.png and b/articles/examples_files/figure-html/umap-57-1.png differ
diff --git a/articles/examples_files/figure-html/umap-D57-1.png b/articles/examples_files/figure-html/umap-D57-1.png
index 8cb419a..5253e29 100644
Binary files a/articles/examples_files/figure-html/umap-D57-1.png and b/articles/examples_files/figure-html/umap-D57-1.png differ
diff --git a/articles/numbering.html b/articles/numbering.html
index 335d135..a5809ac 100644
--- a/articles/numbering.html
+++ b/articles/numbering.html
@@ -90,7 +90,7 @@
 
Introduction
 

 
Kamil Slowikowski

-
2024-05-15

+
2024-06-05

 
The IMGTHLA provides a
 Github repo with alignments of amino acid sequences and nucleotide
 sequences for thousands of alleles of the HLA genes. The IMGTHLA
@@ -194,7 +194,7 @@ 
Numbering indelsHowever, as we move on to CIYNQEE.SV the rule of “add
 10” does not work. Instead of labeling C as position 31, we
 label it position 30. Why?

-
The reason why C is 31, and not 30, is because there is
+
The reason why C is 30, and not 31, is because there is
 an indel (or gap) in the reference sequence at position 25_26 (notice
 the . in R.L). The convention is that
 deletions in the reference sequence are not numbered.

@@ -217,30 +217,38 @@ 
Numbering indels#>  [1] "21"    "22"    "23"    "24"    "25"    "25_26" "26"    "27"    "28"   
 #> [10] "29"    "30"    "31"    "32"    "33"    "34"    "35"    "36"    "36_37"
 #> [19] "37"    "38"    "39"

-
If hlabud is using the correct numbering, then we should see: -
-T at position 21 - C at position 30

+
If hlabud is using the correct numbering, then we should see:

+
    
+
  • 
+T at position 21
    • 
+
  • 
+C at position 30
    • 
+

 
 a$alleles[1,"21"]
-#> [1] "T"
-a$alleles[1,"30"]
+#> [1] "T"

+
+a$alleles[1,"30"]
 #> [1] "C"

 
What do we see at positions 25, 26, and 25_26?

 
Here is the alignment file:

 

 
And here is the result from hlabud:

-
+
 a$alleles[1,"25"]
-#> [1] "R"
-a$alleles[1,"26"]
-#> [1] "L"
-a$alleles[1,"25_26"]
+#> [1] "R"

+
+a$alleles[1,"26"]
+#> [1] "L"

+
+a$alleles[1,"25_26"]
 #> [1] "."

 
So, we can see that the deletion between positions 25 and 26 is not
 numbered like the other residues. Instead, it gets a special label
 (25_26) that consists of the positions flanking the indel (25 and
 26).

 
What alleles do we observe at position 25_26?

-
+
 table(a$alleles[,"25_26"])
 #> 
 #>    .    *    W 
diff --git a/articles/visualize-hla-structure.html b/articles/visualize-hla-structure.html
index f6f296e..515c118 100644
--- a/articles/visualize-hla-structure.html
+++ b/articles/visualize-hla-structure.html
@@ -90,7 +90,7 @@
 
Introduction
 

 
Kamil Slowikowski

-
2024-05-15

+
2024-06-05

 
In this vignette, we explore a few different methods for visualizing
 the molecular structure of HLA proteins. First, we’ll look at an example
 of how to use the NGLVieweR R package to
@@ -215,8 +215,9 @@ 
Using NGLVieweR
 my_alleles <- names(which(a$onehot[,"Y3"] == 1))
 length(my_alleles)
-#> [1] 7023
-head(my_alleles, 20)
+#> [1] 7023

+
+head(my_alleles, 20)
 #>  [1] "B*07:02:01:01" "B*07:02:01:02" "B*07:02:01:03" "B*07:02:01:04"
 #>  [5] "B*07:02:01:05" "B*07:02:01:06" "B*07:02:01:07" "B*07:02:01:08"
 #>  [9] "B*07:02:01:09" "B*07:02:01:10" "B*07:02:01:11" "B*07:02:01:12"
@@ -224,7 +225,7 @@ 
Using NGLVieweR#> [17] "B*07:02:01:17" "B*07:02:01:18" "B*07:02:01:19" "B*07:02:01:20"

 
What fraction of reported HLA-B alleles have tyrosine at IMGT
 position 3 (Y3)?

-
+
 sum(a$onehot[,"Y3"] == 1) / nrow(a$onehot)
 #> [1] 0.711406

 
As it turns out, almost all of the HLA-B alleles have Y3.

@@ -243,31 +244,31 @@ 
Using PyMOL
#!/usr/bin/env bash
-
-# Write a pymol script
-cat << EOF > script.pml
-fetch 7kei
-show cartoon
-remove solvent
-remove chain D
-remove chain H
-color teal, chain A
-color orange, chain B
-color purple, chain C
-color red, chain B & resi 13
-color red, chain B & resi 45
-label n. CA and chain B & resi 13, "%s %s" % (resi, resn)
-label n. CA and chain B & resi 45, "%s %s" % (resi, resn)
-png 7kei.png, width=1200, height=800, dpi=300 
-EOF
-
-# On Linux, we can just use `pymol` without making an alias
-
-# On macOS, we need to make an alias
-alias pymol=/Applications/PyMOL.app/Contents/MacOS/PyMOL
-
-pymol -c script.pml

+
#!/usr/bin/env bash
+
+# Write a pymol script
+cat << EOF > script.pml
+fetch 7kei
+show cartoon
+remove solvent
+remove chain D
+remove chain H
+color teal, chain A
+color orange, chain B
+color purple, chain C
+color red, chain B & resi 13
+color red, chain B & resi 45
+label n. CA and chain B & resi 13, "%s %s" % (resi, resn)
+label n. CA and chain B & resi 45, "%s %s" % (resi, resn)
+png 7kei.png, width=1200, height=800, dpi=300 
+EOF
+
+# On Linux, we can just use `pymol` without making an alias
+
+# On macOS, we need to make an alias
+alias pymol=/Applications/PyMOL.app/Contents/MacOS/PyMOL
+
+pymol -c script.pml

 
Here is what the PyMOL script will do:

 
    
 
  1. Load a structure from the Protein
diff --git a/index.html b/index.html
index 0516a32..3ee8d93 100644
--- a/index.html
+++ b/index.html
@@ -102,13 +102,13 @@ 
    Examples
    Get a one-hot encoded matrix for all HLA-DRB1 alleles
    2. 
 
  2. Convert genotypes to a dosage matrix
    3. 
 
  3. Logistic regression association for amino acid positions
    4. 
-
  4. UMAP embedding of 3,516 HLA-DRB1 alleles
    5. 
+
  5. UMAP embedding of 3,671 HLA-DRB1 alleles
    6. 
 
  6. Get HLA allele frequencies from Allele Frequency Net Database (AFND)
    7. 
 
  7. Compute HLA divergence with the Grantham distance matrix
    8. 
 
  8. Download and unpack all data from the latest IMGTHLA release
    9. 
 
  9. Visualize the 3D molecular structure of HLA proteins and highlight specific amino acid residues
    10. 
 
-
           
    
+
           
    
 

 

 
Citation
diff --git a/pkgdown.yml b/pkgdown.yml
index 6b63d94..cfd9893 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -5,7 +5,7 @@ articles:
   examples: examples.html
   numbering: numbering.html
   visualize-hla-structure: visualize-hla-structure.html
-last_built: 2024-05-15T21:04Z
+last_built: 2024-06-05T18:48Z
 urls:
   reference: https://slowkow.github.io/hlabud/reference
   article: https://slowkow.github.io/hlabud/articles
diff --git a/search.json b/search.json
index 3a026f5..8753527 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://slowkow.github.io/hlabud/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://slowkow.github.io/hlabud/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. General Public Licenses designed make sure freedom distribute copies free software (charge wish), receive source code can get want , can change software use pieces new free programs, know can things. protect rights, need prevent others denying rights asking surrender rights. Therefore, certain responsibilities distribute copies software, modify : responsibilities respect freedom others. example, distribute copies program, whether gratis fee, must pass recipients freedoms received. must make sure , , receive can get source code. must show terms know rights. Developers use GNU GPL protect rights two steps: (1) assert copyright software, (2) offer License giving legal permission copy, distribute /modify . developers’ authors’ protection, GPL clearly explains warranty free software. users’ authors’ sake, GPL requires modified versions marked changed, problems attributed erroneously authors previous versions. devices designed deny users access install run modified versions software inside , although manufacturer can . fundamentally incompatible aim protecting users’ freedom change software. systematic pattern abuse occurs area products individuals use, precisely unacceptable. Therefore, designed version GPL prohibit practice products. problems arise substantially domains, stand ready extend provision domains future versions GPL, needed protect freedom users. Finally, every program threatened constantly software patents. 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This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.  You should have received a copy of the GNU General Public License along with this program.  If not, see .   Copyright (C)    This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"hlabud usage examples","text":"Kamil Slowikowski 2024-05-15 hlabud R package provides functions facilitate download analysis human leukocyte antigen (HLA) genotype sequence alignments IMGTHLA R. Let’s consider question might want answer HLA genotypes. amino acid positions different two genotypes? nucleotides different?","code":"library(hlabud) a <- hla_alignments(\"DRB1\") a$release #> [1] \"3.56.0\" dosage(a$onehot, c(\"DRB1*03:01:05\", \"DRB1*03:02:03\")) #>               F26 Y26 D28 E28 F47 Y47 G86 V86 #> DRB1*03:01:05   0   1   1   0   1   0   0   1 #> DRB1*03:02:03   1   0   0   1   0   1   1   0 n <- hla_alignments(\"DRB1\", type = \"nuc\") n$release #> [1] \"3.56.0\" dosage(n$onehot, c(\"DRB1*03:01:05\", \"DRB1*03:02:03\")) #>               A164 T164 C171 G171 A227 T227 A240 G240 G344 T344 G345 T345 A357 #> DRB1*03:01:05    1    0    1    0    0    1    1    0    0    1    1    0    1 #> DRB1*03:02:03    0    1    0    1    1    0    0    1    1    0    0    1    0 #>               G357 #> DRB1*03:01:05    0 #> DRB1*03:02:03    1"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"installation","dir":"Articles","previous_headings":"","what":"Installation","title":"hlabud usage examples","text":"quickest way get hlabud install GitHub: , included usage examples. hope inspire share HLA analyses. source code page available . Thank reporting issues hlabud.","code":"# install.packages(\"devtools\") devtools::install_github(\"slowkow/hlabud\")"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"get-a-one-hot-encoded-matrix-for-all-hla-drb1-alleles","dir":"Articles","previous_headings":"","what":"Get a one-hot encoded matrix for all HLA-DRB1 alleles","title":"hlabud usage examples","text":"can use hla_alignments(\"DRB1\") load DRB1_prot.txt file latest IMGTHLA release: object list three items: $sequences amino acid sequence alignments named character vector: conventions used alignments (copied EBI help page): entry allele displayed respect reference sequences. identity reference sequence present base displayed hyphen (-). Non-identity reference sequence shown displaying appropriate base position. insertion deletion occurred represented period (.). sequence unknown point alignment, represented asterisk (*). protein alignments null alleles, ‘Stop’ codons represented hash (X). protein alignments, sequence following termination codon, marked appear blank. conventions used nucleotide protein alignments. $alleles matrix amino acids one column position: $onehot one-hot encoded matrix one column amino acid position: one-hot encoded matrix? simple example demonstrate idea:","code":"library(hlabud) a <- hla_alignments(gene = \"DRB1\", verbose = TRUE) #> Reading /home/runner/.local/share/hlabud/3.56.0/alignments/DRB1_prot.txt str(a) #> List of 7 #>  $ sequences: Named chr [1:3671] \"MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGTERVR.LLERCIYNQEE.SVRFDSDVGEYRAVTELGRPDAEYWNSQKDLLEQRRAAVDTYCR\"| __truncated__ \"------------------------------------------------------.-----------.--------------------------------------------\"| __truncated__ \"------------------------------------------------------.-----------.--------------------------------------------\"| __truncated__ \"------------------------------------------------------.-----------.--------------------------------------------\"| __truncated__ ... #>   ..- attr(*, \"names\")= chr [1:3671] \"DRB1*01:01:01:01\" \"DRB1*01:01:01:02\" \"DRB1*01:01:01:03\" \"DRB1*01:01:01:04\" ... #>  $ alleles  : chr [1:3671, 1:288] \"M\" \"M\" \"M\" \"M\" ... #>   ..- attr(*, \"dimnames\")=List of 2 #>   .. ..$ : chr [1:3671] \"DRB1*01:01:01:01\" \"DRB1*01:01:01:02\" \"DRB1*01:01:01:03\" \"DRB1*01:01:01:04\" ... #>   .. ..$ : chr [1:288] \"n29\" \"n28\" \"n27\" \"n26\" ... #>  $ onehot   : num [1:3671, 1:1658] 0 0 0 0 0 0 0 0 0 0 ... #>   ..- attr(*, \"dimnames\")=List of 2 #>   .. ..$ : chr [1:3671] \"DRB1*01:01:01:01\" \"DRB1*01:01:01:02\" \"DRB1*01:01:01:03\" \"DRB1*01:01:01:04\" ... #>   .. ..$ : chr [1:1658] \"n29unk\" \"Mn29\" \"n28unk\" \"Ln28\" ... #>  $ gene     : chr \"DRB1\" #>  $ type     : chr \"prot\" #>  $ release  : chr \"3.56.0\" #>  $ file     : chr \"/home/runner/.local/share/hlabud/3.56.0/alignments/DRB1_prot.txt\" substr(head(a$sequences, 6), 1, 50) #>                                     DRB1*01:01:01:01  #> \"MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGT\"  #>                                     DRB1*01:01:01:02  #> \"--------------------------------------------------\"  #>                                     DRB1*01:01:01:03  #> \"--------------------------------------------------\"  #>                                     DRB1*01:01:01:04  #> \"--------------------------------------------------\"  #>                                     DRB1*01:01:01:05  #> \"--------------------------------------------------\"  #>                                     DRB1*01:01:01:06  #> \"--------------------------------------------------\" a$alleles[1:5,1:40] #>                  n29 n28 n27 n26 n25 n24 n23 n22 n21 n20 n19 n18 n17 n16 n15 #> DRB1*01:01:01:01 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #> DRB1*01:01:01:02 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #> DRB1*01:01:01:03 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #> DRB1*01:01:01:04 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #> DRB1*01:01:01:05 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #>                  n14 n13 n12 n11 n10 n9  n8  n7  n6  n5  n4  n3  n2  n1  1   #> DRB1*01:01:01:01 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #> DRB1*01:01:01:02 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #> DRB1*01:01:01:03 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #> DRB1*01:01:01:04 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #> DRB1*01:01:01:05 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #>                  2   3   4   5   6   7   8   9   10  11  #> DRB1*01:01:01:01 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" #> DRB1*01:01:01:02 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" #> DRB1*01:01:01:03 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" #> DRB1*01:01:01:04 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" #> DRB1*01:01:01:05 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" a$onehot[1:5,1:25] #>                  n29unk Mn29 n28unk Ln28 Vn28 n27unk Cn27 n26unk Ln26 n25unk #> DRB1*01:01:01:01      0    1      0    0    1      0    1      0    1      0 #> DRB1*01:01:01:02      0    1      0    0    1      0    1      0    1      0 #> DRB1*01:01:01:03      0    1      0    0    1      0    1      0    1      0 #> DRB1*01:01:01:04      0    1      0    0    1      0    1      0    1      0 #> DRB1*01:01:01:05      0    1      0    0    1      0    1      0    1      0 #>                  Kn25 Rn25 n24unk Fn24 Ln24 n23unk Pn23 n22unk Gn22 n21unk Cn21 #> DRB1*01:01:01:01    1    0      0    0    1      0    1      0    1      0    0 #> DRB1*01:01:01:02    1    0      0    0    1      0    1      0    1      0    0 #> DRB1*01:01:01:03    1    0      0    0    1      0    1      0    1      0    0 #> DRB1*01:01:01:04    1    0      0    0    1      0    1      0    1      0    0 #> DRB1*01:01:01:05    1    0      0    0    1      0    1      0    1      0    0 #>                  Gn21 n20unk Sn20 n19unk #> DRB1*01:01:01:01    1      0    1      0 #> DRB1*01:01:01:02    1      0    1      0 #> DRB1*01:01:01:03    1      0    1      0 #> DRB1*01:01:01:04    1      0    1      0 #> DRB1*01:01:01:05    1      0    1      0 dat <- data.frame(   V1 = c(\"A\", \"A\", \"B\"),   V2 = c(\"B\", \"B\", \"B\"),   V3 = c(\"C\", \"B\", \"B\"),   stringsAsFactors = TRUE ) dat #>   V1 V2 V3 #> 1  A  B  C #> 2  A  B  B #> 3  B  B  B predict(onehot::onehot(dat), dat) #>      V1=A V1=B V2=B V3=B V3=C #> [1,]    1    0    1    0    1 #> [2,]    1    0    1    1    0 #> [3,]    0    1    1    1    0"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"convert-genotypes-to-a-dosage-matrix","dir":"Articles","previous_headings":"","what":"Convert genotypes to a dosage matrix","title":"hlabud usage examples","text":"Suppose individuals following genotypes: want run association test amino acid positions, need convert genotype names matrix allele dosages (e.g., 0, 1, 2). can use dosage() convert individual’s genotypes amino acid dosages: Note: dosage matrix one row individual one column amino acid position. default, dosage() discard columns individuals identical. input allele names truncated 4-digits 2-digits (e.g. DRB1*03:01 DRB1*03), hlabud pick first allele matches input allele (e.g. DRB1*03:01:01:01). want specific allele, need provide full allele name input. Please careful check data looks way expect!","code":"genotypes <- c(   \"DRB1*12:02:02:03,DRB1*12:02:02:03\",   \"DRB1*04:174,DRB1*15:152\",   \"DRB1*04:56:02,DRB1*15:01:48\",   \"DRB1*14:172,DRB1*04:160\",   \"DRB1*04:359,DRB1*04:284:02\" ) dosage <- dosage(a$onehot, genotypes) dosage[,1:8] #>                                   n29unk Mn29 n28unk Vn28 n27unk Cn27 n26unk #> DRB1*12:02:02:03,DRB1*12:02:02:03      0    2      0    2      0    2      0 #> DRB1*04:174,DRB1*15:152                2    0      2    0      2    0      2 #> DRB1*04:56:02,DRB1*15:01:48            2    0      2    0      2    0      2 #> DRB1*14:172,DRB1*04:160                2    0      2    0      2    0      2 #> DRB1*04:359,DRB1*04:284:02             2    0      2    0      2    0      2 #>                                   Ln26 #> DRB1*12:02:02:03,DRB1*12:02:02:03    2 #> DRB1*04:174,DRB1*15:152              0 #> DRB1*04:56:02,DRB1*15:01:48          0 #> DRB1*14:172,DRB1*04:160              0 #> DRB1*04:359,DRB1*04:284:02           0 dim(dosage) #> [1]   5 428"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"logistic-regression-association-for-amino-acid-positions","dir":"Articles","previous_headings":"","what":"Logistic regression association for amino acid positions","title":"hlabud usage examples","text":"Let’s simulate dataset cases controls demonstrate one approach testing amino acid positions might associated cases. simulated dataset 100 individuals, 52 cases 48 controls. also one column amino acid position might want test association case variable. One possible approach association testing use glm() fit logistic regression model amino acid position. reveal amino acid position might associated case variable simulated dataset. volcano shows Odds Ratio P-value amino acid position. top hits P < 0.05 labeled.  simulation, case variable associated F37 (P = 0.021, = 4, 95% CI 1.4 15).","code":"set.seed(2) n <- 100 d <- data.frame(   geno = paste(     sample(rownames(a$onehot), n, replace = TRUE),     sample(rownames(a$onehot), n, replace = TRUE),     sep = \",\"   ),   age = sample(21:100, n, replace = TRUE),   case = sample(0:1, n, replace = TRUE) ) d <- cbind(d, dosage(a$onehot, d$geno)) d[1:5,1:6] #>                                                          geno age case n29unk #> DRB1*04:243,DRB1*15:01:01:08     DRB1*04:243,DRB1*15:01:01:08  67    0      1 #> DRB1*04:08:01:01,DRB1*04:56:02 DRB1*04:08:01:01,DRB1*04:56:02  38    1      1 #> DRB1*13:339,DRB1*04:112               DRB1*13:339,DRB1*04:112  67    0      2 #> DRB1*03:85,DRB1*01:02:10             DRB1*03:85,DRB1*01:02:10  55    0      2 #> DRB1*03:62,DRB1*14:224                 DRB1*03:62,DRB1*14:224  73    1      1 #>                                Mn29 n28unk #> DRB1*04:243,DRB1*15:01:01:08      1      1 #> DRB1*04:08:01:01,DRB1*04:56:02    1      1 #> DRB1*13:339,DRB1*04:112           0      2 #> DRB1*03:85,DRB1*01:02:10          0      2 #> DRB1*03:62,DRB1*14:224            1      1 # prepare column names for use in formulas ix <- 4:ncol(d) colnames(d)[ix] <- sprintf(\"VAR%s\", colnames(d)[ix])  # select the amino acid positions that have at least 3 people with dosage > 0 my_as <- names(which(colSums(d[,4:ncol(d)] > 0) >= 3))  # run the association tests my_glm <- rbindlist(pblapply(my_as, function(my_a) {   f <- sprintf(\"case ~ %s\", my_a)   glm(as.formula(f), data = d, family = \"binomial\") %>%     parameters(exponentiate = TRUE) }))  # look at the top hits my_glm %>%   arrange(p) %>%   filter(!Parameter %in% c(\"(Intercept)\")) %>%   head #>    Parameter Coefficient        SE    CI     CI_low    CI_high         z #>                                      #> 1:    VARF37   3.9529448 2.3501312  0.95 1.35121582 14.6317263  2.311857 #> 2:    VARY60   0.4269585 0.1790904  0.95 0.18053396  0.9458131 -2.028981 #> 3:    VARK98   0.5739907 0.1603272  0.95 0.32635370  0.9824460 -1.987475 #> 4:   VARS104   0.5739907 0.1603272  0.95 0.32635370  0.9824460 -1.987475 #> 5:    VARQ96   0.3253919 0.1886793  0.95 0.08932709  0.9191775 -1.936226 #> 6:   VARS179   0.6085247 0.1617164  0.95 0.35644231  1.0163414 -1.869106 #>    df_error          p #>              #> 1:      Inf 0.02078556 #> 2:      Inf 0.04246025 #> 3:      Inf 0.04686976 #> 4:      Inf 0.04686976 #> 5:      Inf 0.05284007 #> 6:      Inf 0.06160809"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"umap-embedding-of-hla-drb1-alleles","dir":"Articles","previous_headings":"","what":"UMAP embedding of HLA-DRB1 alleles","title":"hlabud usage examples","text":"many possibilities analysis one-hot encoding matrix. example, UMAP embedding HLA-DRB1 alleles encoded one-hot amino acid matrix 1658 columns, one amino acid position. color indicates 2-digit allele name.  can highlight alleles aspartic acid (Asp D) position 57:  can use color represent amino acid residue position 57:","code":"uamp(a$onehot, n_epochs = 200, min_dist = 1, spread = 2)"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"get-hla-allele-frequencies-from-allele-frequency-net-database-afnd","dir":"Articles","previous_headings":"","what":"Get HLA allele frequencies from Allele Frequency Net Database (AFND)","title":"hlabud usage examples","text":"hlabud R package includes table HLA allele frequencies Allele Frequency Net Database (AFND). use data, please cite latest manuscript Allele Frequency Net Database: Gonzalez-Galarza FF, McCabe , Santos EJMD, Jones J, Takeshita L, Ortega-Rivera ND, et al. Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data new query tools. Nucleic Acids Res. 2020;48: D783–D788. doi:10.1093/nar/gkz1029 can use data plot frequency specific allele (e.g. DQB1*02:01) populations 1000 sampled individuals:  See github.com/slowkow/allelefrequencies examples might use data.","code":"af <- hla_frequencies() af #> # A tibble: 123,502 × 7 #>    group gene  allele  population            indivs_over_n alleles_over_2n     n #>                                               #>  1 hla   A     A*01:01 Argentina Rosario To…          15.1           0.076    86 #>  2 hla   A     A*01:01 Armenia combined Reg…          NA             0.125   100 #>  3 hla   A     A*01:01 Australia Cape York …          NA             0.053   103 #>  4 hla   A     A*01:01 Australia Groote Eyl…          NA             0.027    75 #>  5 hla   A     A*01:01 Australia New South …          NA             0.187   134 #>  6 hla   A     A*01:01 Australia Yuendumu A…          NA             0.008   191 #>  7 hla   A     A*01:01 Austria                        27             0.146   200 #>  8 hla   A     A*01:01 Azores Central Islan…          NA             0.08     59 #>  9 hla   A     A*01:01 Azores Oriental Isla…          NA             0.115    43 #> 10 hla   A     A*01:01 Azores Terceira Isla…          NA             0.109   130 #> # ℹ 123,492 more rows my_allele <- \"DQB1*02:01\" my_af <- af %>% filter(allele == my_allele) %>%   filter(n > 1000) %>%   arrange(-alleles_over_2n)  ggplot(my_af) +   aes(x = alleles_over_2n, y = reorder(population, alleles_over_2n)) +   scale_y_discrete(position = \"right\") +   geom_colh() +   labs(     x = \"Allele Frequency (Alleles / 2N)\",     y = NULL,     title =  glue(\"Frequency of {my_allele} across {length(unique(my_af$population))} populations\"),     caption = \"Data from AFND http://allelefrequencies.net\"   )"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"compute-hla-divergence-with-the-grantham-distance-matrix","dir":"Articles","previous_headings":"","what":"Compute HLA divergence with the Grantham distance matrix","title":"hlabud usage examples","text":"Humans diploid, us two copies HLA gene. individual two highly dissimilar alleles can bind greater number different peptides homozygous individual (https://doi.org/10.1007/BF02918202): MHC class II allele capacity bind present specific set peptides processed antigens. inability specific class II allele bind present fragment derived processed antigen results loss immune responsiveness antigen individuals homozygous class II allele. amino acid distance matrix Granthan 1974 (https://doi.org/10.1126/science.185.4154.862) encodes information composition, polarity, molecular volume amino acid. can use matrix compute HLA divergence metric set individuals like : divergence homozygote equal zero, definition: hlabud includes R code divergence calculations translated original Perl code Pierini & Lenz 2018 (https://doi.org/10.1093/molbev/msy116). amino acid distance matrix easily accessible, provide two built-options “grantham” “uniform”:","code":"grantham #>    amino    c    p     v #> 1    Ser 1.42  9.2  32.0 #> 2    Arg 0.65 10.5 124.0 #> 3    Leu 0.00  4.9 111.0 #> 4    Pro 0.39  8.0  32.5 #> 5    Thr 0.71  8.6  61.0 #> 6    Ala 0.00  8.1  31.0 #> 7    Val 0.00  5.9  84.0 #> 8    Gly 0.74  9.0   3.0 #> 9    Ile 0.00  5.2 111.0 #> 10   Phe 0.00  5.2 132.0 #> 11   Tyr 0.20  6.2 136.0 #> 12   Cys 2.75  5.5  55.0 #> 13   His 0.58 10.4  96.0 #> 14   Gln 0.89 10.5  85.0 #> 15   Asn 1.33 11.6  56.0 #> 16   Lys 0.33 11.3 119.0 #> 17   Asp 1.38 13.0  54.0 #> 18   Glu 0.92 12.3  83.0 #> 19   Met 0.00  5.7 105.0 #> 20   Trp 0.13  5.4 170.0 my_genos <- c(\"A*23:01:12,A*24:550\", \"A*25:12N,A*11:27\", \"A*24:381,A*33:85\")  hla_divergence(my_genos) #> A*23:01:12,A*24:550    A*25:12N,A*11:27    A*24:381,A*33:85  #>           0.5131579           3.4736842           5.1078947 hla_divergence(\"A*01:01,A*01:01\") #> A*01:01,A*01:01  #>               0 amino_distance_matrix(method = \"grantham\") #>     A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y #> A   0 112 111 126 195  91 107  60  86  94  96 106  84 113  27  99  58 148 112 #> R 112   0  86  96 180  43  54 125  29  97 102  26  91  97 103 110  71 101  77 #> N 111  86   0  23 139  46  42  80  68 149 153  94 142 158  91  46  65 174 143 #> D 126  96  23   0 154  61  45  94  81 168 172 101 160 177 108  65  85 181 160 #> C 195 180 139 154   0 154 170 159 174 198 198 202 196 205 169 112 149 215 194 #> Q  91  43  46  61 154   0  29  87  24 109 113  53 101 116  76  68  42 130  99 #> E 107  54  42  45 170  29   0  98  40 134 138  56 126 140  93  80  65 152 122 #> G  60 125  80  94 159  87  98   0  98 135 138 127 127 153  42  56  59 184 147 #> H  86  29  68  81 174  24  40  98   0  94  99  32  87 100  77  89  47 115  83 #> I  94  97 149 168 198 109 134 135  94   0   5 102  10  21  95 142  89  61  33 #> L  96 102 153 172 198 113 138 138  99   5   0 107  15  22  98 145  92  61  36 #> K 106  26  94 101 202  53  56 127  32 102 107   0  95 102 103 121  78 110  85 #> M  84  91 142 160 196 101 126 127  87  10  15  95   0  28  87 135  81  67  36 #> F 113  97 158 177 205 116 140 153 100  21  22 102  28   0 114 155 103  40  22 #> P  27 103  91 108 169  76  93  42  77  95  98 103  87 114   0  74  38 147 110 #> S  99 110  46  65 112  68  80  56  89 142 145 121 135 155  74   0  58 177 144 #> T  58  71  65  85 149  42  65  59  47  89  92  78  81 103  38  58   0 128  92 #> W 148 101 174 181 215 130 152 184 115  61  61 110  67  40 147 177 128   0  37 #> Y 112  77 143 160 194  99 122 147  83  33  36  85  36  22 110 144  92  37   0 #> V  64  96 133 152 192  96 121 109  84  29  32  97  21  50  68 124  69  88  55 #>     V #> A  64 #> R  96 #> N 133 #> D 152 #> C 192 #> Q  96 #> E 121 #> G 109 #> H  84 #> I  29 #> L  32 #> K  97 #> M  21 #> F  50 #> P  68 #> S 124 #> T  69 #> W  88 #> Y  55 #> V   0"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"download-and-unpack-all-data-from-the-latest-imgthla-release","dir":"Articles","previous_headings":"","what":"Download and unpack all data from the latest IMGTHLA release","title":"hlabud usage examples","text":"want use hla_alignments(), don’t need install_hla() data files downloaded automatically needed cached future use. users might need access additional files present full data release. Run install_hla() download unpack latest IMGTHLA release. destination folder downloaded data files getOption(\"hlabud_dir\") (automatically tailored operating system thanks rappdirs package). examples download releases get list release names. Download latest release (default) specific release: Optionally, get set directory hlabud uses store data: installing releases, hlabud folder might look like :","code":"# Download all of the data (120MB) for the latest IMGTHLA release install_hla(release = \"latest\")  # Download a specific release install_hla(release = \"3.51.0\") getOption(\"hlabud_dir\") #> [1] \"/home/username/.local/share/hlabud\"  # Manually override the directory for hlabud to use options(hlabud_dir = \"/path/to/my/dir\") ❯ ls -lah \"/home/user/.local/share/hlabud\" total 207M drwxrwxr-x  3 user user      32 Apr  5 01:19 3.30.0 drwxrwxr-x 11 user user    4.0K Apr  7 19:31 3.40.0 drwxrwxr-x 12 user user    4.0K Apr  5 00:27 3.51.0 -rw-rw-r--  1 user user     15K Apr  7 19:23 tags.json -rw-rw-r--  1 user user     79M Apr  7 19:28 v3.40.0-alpha.tar.gz -rw-rw-r--  1 user user    129M Apr  4 20:07 v3.51.0-alpha.tar.gz"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"count-the-number-of-alleles-in-each-imgthla-release","dir":"Articles","previous_headings":"","what":"Count the number of alleles in each IMGTHLA release","title":"hlabud usage examples","text":"can get list release names: can get allele names release: Next, count many alleles release: plot number alleles line plot:","code":"releases <- hla_releases() releases #>  [1] \"3.56.0\"   \"3.55.0\"   \"3.54.0\"   \"3.53.0\"   \"3.52.0\"   \"3.51.0\"   #>  [7] \"3.50.0\"   \"3.49.0\"   \"3.48.0\"   \"3.47.0\"   \"3.46.0\"   \"3.45.1\"   #> [13] \"3.45.01\"  \"3.45.0.1\" \"3.45.0\"   \"3.44.1\"   \"3.44.0\"   \"3.43.0\"   #> [19] \"3.42.0\"   \"3.41.2\"   \"3.41.0\"   \"3.40.0\"   \"3.39.0\"   \"3.38.0\"   #> [25] \"3.37.0\"   \"3.36.0\"   \"3.35.0\"   \"3.34.0\"   \"3.33.0\"   \"3.32.0\" my_alleles <- rbindlist(lapply(releases, function(release) {   retval <- hla_alleles(release = release)   retval$release <- release   return(retval) }), fill = TRUE) #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.3451.txt' #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.34501.txt' #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.34501.txt' #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.3441.txt' #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.3412.txt' d <- my_alleles %>% count(release) %>% filter(n > 1) d #>     release     n #>        #>  1:  3.32.0 18363 #>  2:  3.33.0 18955 #>  3:  3.34.0 20272 #>  4:  3.35.0 21683 #>  5:  3.36.0 22548 #>  6:  3.37.0 24093 #>  7:  3.38.0 25958 #>  8:  3.39.0 26512 #>  9:  3.40.0 27273 #> 10:  3.41.0 27980 #> 11:  3.42.0 28786 #> 12:  3.43.0 29417 #> 13:  3.44.0 30523 #> 14:  3.45.0 31552 #> 15:  3.46.0 32330 #> 16:  3.47.0 33552 #> 17:  3.48.0 34145 #> 18:  3.49.0 35077 #> 19:  3.50.0 36016 #> 20:  3.51.0 36625 #> 21:  3.52.0 37068 #> 22:  3.53.0 37619 #> 23:  3.54.0 38416 #> 24:  3.55.0 38909 #> 25:  3.56.0 39886 #>     release     n ggplot(d) +   aes(x = release, y = n, group = 1) +   geom_line() +   geom_text(aes(label = release), hjust = 1) +   labs(x = NULL, y = \"Number of alleles\",   title = \"Each release has more HLA alleles\") +   theme(     axis.text.x = element_blank(),     axis.ticks.x = element_blank(),   ) d2 <- my_alleles %>% mutate(gene = str_split_fixed(Allele, \"\\\\*\", 2)[,1]) %>% count(release, gene) ggplot() +   aes(x = release, y = n) +   geom_line(     data = d2,     aes(group = gene, color = gene)   ) +   scale_color_discrete(guide = \"none\") +   geom_text(     data = d2 %>% filter(release == \"3.52.0\"),     mapping = aes(label = gene),     hjust = 0   ) +   labs(x = NULL, y = \"Number of alleles\",   title = \"Number of alleles per release and gene\") +   scale_x_discrete(expand = expansion(mult = c(0.01, 0.1))) +   scale_y_log10() +   theme(     panel.grid.major.y = element_line(),      axis.text.x = element_blank(),     axis.ticks.x = element_blank(),   )"},{"path":"https://slowkow.github.io/hlabud/articles/numbering.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Numbering amino acid positions","text":"Kamil Slowikowski 2024-05-15 IMGTHLA provides Github repo alignments amino acid sequences nucleotide sequences thousands alleles HLA genes. IMGTHLA alignments define official numbering scheme, provide explanations conventions help page. hlabud R package provides easy access alignment data, hlabud follows official numbering scheme. examples help beginners visualize understand conventions work.","code":""},{"path":"https://slowkow.github.io/hlabud/articles/numbering.html","id":"alignment-files-on-the-imgthla-github-page","dir":"Articles","previous_headings":"","what":"Alignment files on the IMGTHLA Github page","title":"Numbering amino acid positions","text":"IMGTHLA Github page provides folder alignment files.  examples vignette, use HLA-DRB1 gene. DRB1, can find three separate files: https://raw.githubusercontent.com/ANHIG/IMGTHLA/v3.56.0-alpha/alignments/DRB1_gen.txt https://raw.githubusercontent.com/ANHIG/IMGTHLA/v3.56.0-alpha/alignments/DRB1_nuc.txt https://raw.githubusercontent.com/ANHIG/IMGTHLA/v3.56.0-alpha/alignments/DRB1_prot.txt files contain different information: gen contains genomic DNA sequences. nuc contains nucleotide coding sequences (CDS). prot contains protein sequences (amino acids). Let’s consider DRB1_prot.txt file. file look like?  plain text file header sequence alignments. alignment, line represents one sequence (allele), line 100 residues. first 100 residues alleles shown first block. , next block next 100 residues alleles, .","code":""},{"path":"https://slowkow.github.io/hlabud/articles/numbering.html","id":"numbering-conventions","dir":"Articles","previous_headings":"Alignment files on the IMGTHLA Github page","what":"Numbering conventions","title":"Numbering amino acid positions","text":"conventions used alignments (copied EBI): entry allele displayed respect reference sequences. identity reference sequence present base displayed hyphen (-). Non-identity reference sequence shown displaying appropriate base position. insertion deletion occurred represented period (.). sequence unknown point alignment, represented asterisk (*). protein alignments null alleles, ‘Stop’ codons represented hash (X). protein alignments, sequence following termination codon, marked appear blank. conventions used nucleotide protein alignments. ’s lot information! Let’s try work example illustrate works. first sequence alignment reference sequence. position numbering relative reference sequence. means deletions (.) reference sequence numbered. Notice numbering starts negative numbers. help page clarifies: Protein Sequence Numbering amino acid-based systems, start codon mature protein labeled codon 1. codon 5’ numbered -1. numbering based reference sequence. amino acid number 0.","code":""},{"path":"https://slowkow.github.io/hlabud/articles/numbering.html","id":"numbering-indels","dir":"Articles","previous_headings":"Alignment files on the IMGTHLA Github page","what":"Numbering indels","title":"Numbering amino acid positions","text":"alignment shows 100 residues displayed chunks 10:  numbering convention says indels reference sequence numbered. clarify point, manually added additional numbers (11, 21, 30, 39, 49, 59) alignment :  Notice move first chunk GDTRPRFLWQ next chunk LKFECHFFNG simply add 10 1 get 11 number L amino acid. , move TERVR.LLER, add 10 11 get 21 T amino acid. However, move CIYNQEE.SV rule “add 10” work. Instead labeling C position 31, label position 30. ? reason C 31, 30, indel (gap) reference sequence position 25_26 (notice . R.L). convention deletions reference sequence numbered. Let’s take closer look data hlabud. first amino acid positions first 4 sequences: hlabud numbers positions focusing example: hlabud using correct numbering, see: - T position 21 - C position 30 see positions 25, 26, 25_26? alignment file:  result hlabud: , can see deletion positions 25 26 numbered like residues. Instead, gets special label (25_26) consists positions flanking indel (25 26). alleles observe position 25_26? three possibilities position 25_26: . indicates deletion 1 amino acid (absence amino position) * indicates sequence unknown position W indicates tryptophan position hope example helps explain numbering indels. notice discrepancy hlabud IMGT, please report .","code":"library(hlabud) a <- hla_alignments(\"DRB1\", release = \"3.56.0\") seqs <- substr(a$sequences[1:4], 30, 89) str_replace_all(seqs, \"(\\\\S{10})\", \"\\\\1 \") #> [1] \"GDTRPRFLWQ LKFECHFFNG TERVR.LLER CIYNQEE.SV RFDSDVGEYR AVTELGRPDA \" #> [2] \"---------- ---------- -----.---- -------.-- ---------- ---------- \" #> [3] \"---------- ---------- -----.---- -------.-- ---------- ---------- \" #> [4] \"---------- ---------- -----.---- -------.-- ---------- ---------- \" colnames(a$alleles)[50:70] #>  [1] \"21\"    \"22\"    \"23\"    \"24\"    \"25\"    \"25_26\" \"26\"    \"27\"    \"28\"    #> [10] \"29\"    \"30\"    \"31\"    \"32\"    \"33\"    \"34\"    \"35\"    \"36\"    \"36_37\" #> [19] \"37\"    \"38\"    \"39\" a$alleles[1,\"21\"] #> [1] \"T\" a$alleles[1,\"30\"] #> [1] \"C\" a$alleles[1,\"25\"] #> [1] \"R\" a$alleles[1,\"26\"] #> [1] \"L\" a$alleles[1,\"25_26\"] #> [1] \".\" table(a$alleles[,\"25_26\"]) #>  #>    .    *    W  #> 3658   12    1"},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Visualize HLA protein structures","text":"Kamil Slowikowski 2024-05-15 vignette, explore different methods visualizing molecular structure HLA proteins. First, ’ll look example use NGLVieweR R package show HLA protein structures. Next, ’ll use PyMOL thing.","code":""},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"what-are-the-pdb-identifiers-for-each-hla-gene","dir":"Articles","previous_headings":"","what":"What are the PDB identifiers for each HLA gene?","title":"Visualize HLA protein structures","text":"list PDB identifiers might consider using represent HLA protein: Also try searching PDB website , e.g., \"HLA-DR\" see appropriate structure analysis.","code":"HLA-A  2xpg HLA-B  2bvp HLA-C  4nt6 HLA-DP 3lqz HLA-DQ 4z7w HLA-DR 3pdo"},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"using-nglviewer","dir":"Articles","previous_headings":"","what":"Using NGLVieweR","title":"Visualize HLA protein structures","text":"Let’s try visualize amino acid PDB position 9 HLA-B protein structure. visualize structure 2bvp Protein Data Bank (PDB). example NGLVieweR R package Niels van der Velden: view , see blue peptide red HLA-B protein. tyrosine PDB position 9 highlighted ball+stick representation, also labeled text label. structure rotating can getter better view. can use hlabud answer questions HLA-B amino acid sequence. first question need ask : IMGT position corresponds tyrosine PDB position 9? need open PDB Sequence Annotations tool order figure IMGT number corresponds PDB number 9. screenshot tool: Next, can view amino acid sequence numbering IMGT: eye, can see sequence YFYT starting PDB position 9 corresponds YFYT sequence IMGT position 3. , manually confirmed PDB position 9 matches IMGT position 3. Next, might ask HLA-B alleles Y3? fraction reported HLA-B alleles tyrosine IMGT position 3 (Y3)? turns , almost HLA-B alleles Y3.","code":"# devtools::install_github(\"nvelden/NGLVieweR\") # we need the latest version library(NGLVieweR) library(magrittr) my_sele <- \"9:A\" NGLVieweR(\"2bvp\") %>%   stageParameters(     backgroundColor = \"white\",     zoomSpeed = 1,     cameraFov = 80   ) %>%   addRepresentation(     type = \"cartoon\"   ) %>%   addRepresentation(     type = \"ball+stick\",     param = list(       sele = my_sele     )   ) %>%   addRepresentation(     type = \"label\",     param = list(       sele = my_sele,       labelType = \"format\",       labelFormat = \"[%(resname)s]%(resno)s\", # or enter custom text       labelGrouping = \"residue\", # or \"atom\" (eg. sele = \"20:A.CB\")       color = \"black\",       fontFamiliy = \"sans-serif\",       xOffset = 1,       yOffset = 0,       zOffset = 0,       fixedSize = TRUE,       radiusType = 1,       radiusSize = 5.5, # Label size       showBackground = TRUE       # backgroundColor=\"black\",       # backgroundOpacity=0.5     )   ) %>%   zoomMove(     center = my_sele,     zoom = my_sele,     duration = 0, # animation time in ms     z_offSet = -20   ) %>%   setSpin() library(hlabud) a <- hla_alignments(\"B\") library(stringr) a$alleles[which(str_detect(rownames(a$alleles), \"B*57:03\")),][1,1:50] #>      n30      n29      n28      n27      n26      n25      n24      n23  #>      \"M\"      \"R\"      \"V\"      \"T\"      \"A\"      \"P\"      \"R\"      \"T\"  #>      n22  n22_n21      n21      n20      n19      n18      n17      n16  #>      \"V\" \"......\"      \"L\"      \"L\"      \"L\"      \"L\"      \"W\"      \"G\"  #>      n15      n14      n13      n12      n11      n10       n9       n8  #>      \"A\"      \"V\"      \"A\"      \"L\"      \"T\"      \"E\"      \"T\"      \"W\"  #>       n7       n6       n5       n4       n3       n2       n1        1  #>      \"A\"      \"G\"      \"S\"      \"H\"      \"S\"      \"M\"      \"R\"      \"Y\"  #>        2        3        4        5        6        7        8        9  #>      \"F\"      \"Y\"      \"T\"      \"A\"      \"M\"      \"S\"      \"R\"      \"P\"  #>       10       11       12       13       14       15       16       17  #>      \"G\"      \"R\"      \"G\"      \"E\"      \"P\"      \"R\"      \"F\"      \"I\"  #>       18    18_19  #>      \"A\"  \".....\" my_alleles <- names(which(a$onehot[,\"Y3\"] == 1)) length(my_alleles) #> [1] 7023 head(my_alleles, 20) #>  [1] \"B*07:02:01:01\" \"B*07:02:01:02\" \"B*07:02:01:03\" \"B*07:02:01:04\" #>  [5] \"B*07:02:01:05\" \"B*07:02:01:06\" \"B*07:02:01:07\" \"B*07:02:01:08\" #>  [9] \"B*07:02:01:09\" \"B*07:02:01:10\" \"B*07:02:01:11\" \"B*07:02:01:12\" #> [13] \"B*07:02:01:13\" \"B*07:02:01:14\" \"B*07:02:01:15\" \"B*07:02:01:16\" #> [17] \"B*07:02:01:17\" \"B*07:02:01:18\" \"B*07:02:01:19\" \"B*07:02:01:20\" sum(a$onehot[,\"Y3\"] == 1) / nrow(a$onehot) #> [1] 0.711406"},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"using-pymol","dir":"Articles","previous_headings":"","what":"Using PyMOL","title":"Visualize HLA protein structures","text":"PyMOL one favorite methods visualizing protein structures, allows us change residue existing protein visualize new mutated protein. takes lines PyMOL create nice figure. example, want quickly highlight positions 13 45 HLA-DQB1, snippet PyMOL code produce figure . Bash script : Write PyMOL script Run PyMOL script pymol command PyMOL script : Load structure Protein Data Bank (PDB). 7kei identifier published protein structure. Color HLA-DQA1 protein teal. Color HLA-DQB1 protein orange. Color peptide purple. color residues 13 45 HLA-DQB1 red. Label residues positions names. Write PNG file view structure.  image , manually rotated structure mouse added text labels like \"PDB: 7kei\" saving file.","code":"#!/usr/bin/env bash  # Write a pymol script cat << EOF > script.pml fetch 7kei show cartoon remove solvent remove chain D remove chain H color teal, chain A color orange, chain B color purple, chain C color red, chain B & resi 13 color red, chain B & resi 45 label n. CA and chain B & resi 13, \"%s %s\" % (resi, resn) label n. CA and chain B & resi 45, \"%s %s\" % (resi, resn) png 7kei.png, width=1200, height=800, dpi=300  EOF  # On Linux, we can just use `pymol` without making an alias  # On macOS, we need to make an alias alias pymol=/Applications/PyMOL.app/Contents/MacOS/PyMOL  pymol -c script.pml"},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"other-software-for-viewing-pdb-data","dir":"Articles","previous_headings":"","what":"Other software for viewing PDB data","title":"Visualize HLA protein structures","text":"ChimeraX: https://www.cgl.ucsf.edu/chimerax/ Python: https://github.com/nglviewer/nglview Javascript: https://www.rcsb.org/3d-view https://www.ncbi.nlm.nih.gov/Structure/icn3d/full.html?mmdbid=7kei&bu=1 https://github.com/nglviewer/ngl https://github.com/biasmv/pv R: https://www.raymolecule.com","code":""},{"path":"https://slowkow.github.io/hlabud/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Kamil Slowikowski. Author, maintainer.","code":""},{"path":"https://slowkow.github.io/hlabud/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"J R, DJ B, X G, MA C, P F, SGE. M (2019). “IPD-IMGT/HLA Database.” Nucleic Acids Research, 48(D1), D948–D955. doi:10.1093/nar/gkz950. Slowikowski K (2023). hlabud: IMGTHLA Data R. doi:10.5281/zenodo.8183949, R package version 2.0.0, https://github.com/slowkow/hlabud.","code":"@Article{,   author = {Robinson J and Barker DJ and Georgiou X and Cooper MA and Flicek P and Marsh SGE.},   title = {IPD-IMGT/HLA Database},   doi = {10.1093/nar/gkz950},   year = {2019},   month = {oct},   publisher = {Oxford University Press},   volume = {48},   number = {D1},   pages = {D948–D955},   journal = {Nucleic Acids Research}, } @Manual{,   title = {{hlabud}: IMGTHLA Data from R},   author = {Kamil Slowikowski},   year = {2023},   note = {R package version 2.0.0},   doi = {10.5281/zenodo.8183949},   url = {https://github.com/slowkow/hlabud}, }"},{"path":"https://slowkow.github.io/hlabud/index.html","id":"hlabud-hla-analysis-in-r-","dir":"","previous_headings":"","what":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"hlabud provides methods retrieve sequence alignment data IMGTHLA convert data convenient R matrices ready downstream analysis. See usage examples learn use data logistic regression dimensionality reduction. example, let’s consider simple question two HLA genotypes. amino acid positions different two genotypes? output, can conclude four positions (26, 28, 47, 86) distinguish two HLA-DRB1 alleles. see DRB1*03:01:05 Y position 26 DRB1*03:02:03 F.","code":"library(hlabud) a <- hla_alignments(\"DRB1\") dosage(a$onehot, c(\"DRB1*03:01:05\", \"DRB1*03:02:03\"))  ##               F26 Y26 D28 E28 F47 Y47 G86 V86 ## DRB1*03:01:05   0   1   1   0   1   0   0   1 ## DRB1*03:02:03   1   0   0   1   0   1   1   0"},{"path":"https://slowkow.github.io/hlabud/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"quickest way get hlabud install GitHub:","code":"# install.packages(\"devtools\") devtools::install_github(\"slowkow/hlabud\")"},{"path":"https://slowkow.github.io/hlabud/index.html","id":"examples","dir":"","previous_headings":"","what":"Examples","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"See usage examples get ideas use hlabud analyses. Get one-hot encoded matrix HLA-DRB1 alleles Convert genotypes dosage matrix Logistic regression association amino acid positions UMAP embedding 3,516 HLA-DRB1 alleles Get HLA allele frequencies Allele Frequency Net Database (AFND) Compute HLA divergence Grantham distance matrix Download unpack data latest IMGTHLA release Visualize 3D molecular structure HLA proteins highlight specific amino acid residues","code":""},{"path":"https://slowkow.github.io/hlabud/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"hlabud provides access data IMGT/HLA database. Therefore, use hlabud please cite IMGT/HLA paper: Robinson J, Barker DJ, Georgiou X, Cooper MA, Flicek P, Marsh SGE. IPD-IMGT/HLA Database. Nucleic Acids Res. 2020;48: D948–D955. doi:10.1093/nar/gkz950 hlabud also provides access data Allele Frequency Net Database (AFND). Therefore, use hlabud::hla_frequencies() please cite AFND paper: Gonzalez-Galarza FF, McCabe , Santos EJMD, Jones J, Takeshita L, Ortega-Rivera ND, et al. Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data new query tools. Nucleic Acids Res. 2020;48: D783–D788. doi:10.1093/nar/gkz1029 Additionally, can also cite hlabud package like : Slowikowski K. hlabud: methods access analysis human leukocyte antigen (HLA) gene sequence alignments IMGT/HLA. R package version 1.0.0.","code":""},{"path":"https://slowkow.github.io/hlabud/index.html","id":"related-work","dir":"","previous_headings":"","what":"Related work","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"recommend article anyone new HLA, beautiful figures help build intuition: La Gruta NL, Gras S, Daley SR, Thomas PG, Rossjohn J. Understanding drivers MHC restriction T cell receptors. Nat Rev Immunol. 2018;18: 467–478. Learn conventions HLA nomenclature: Marsh SGE, Albert ED, Bodmer WF, Bontrop RE, Dupont B, Erlich HA, et al. Nomenclature factors HLA system, 2010. Tissue Antigens. 2010;75: 291–455. case-control analysis HLA genotype data, consider BIGDAWG R package available CRAN. related article: Pappas DJ, Marin W, Hollenbach JA, Mack SJ. Bridging ImmunoGenomic Data Analysis Workflow Gaps (BIGDAWG): integrated case-control analysis pipeline. Hum Immunol. 2016;77: 283–287.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"default, return amino acid distance matrix Grantham 1974 (doi:10.1126/science.185.4154.862).","code":""},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"","code":"amino_distance_matrix(method = \"grantham\")"},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"method \"grantham\" Grantham 1974 matrix \"uniform\" matrix ones non-diagonal.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"20x20 symmetric matrix positive numbers zeros diagonal.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"","code":"# By default, the Grantham 1974 matrix amino_distance_matrix(\"grantham\") #>     A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y #> A   0 112 111 126 195  91 107  60  86  94  96 106  84 113  27  99  58 148 112 #> R 112   0  86  96 180  43  54 125  29  97 102  26  91  97 103 110  71 101  77 #> N 111  86   0  23 139  46  42  80  68 149 153  94 142 158  91  46  65 174 143 #> D 126  96  23   0 154  61  45  94  81 168 172 101 160 177 108  65  85 181 160 #> C 195 180 139 154   0 154 170 159 174 198 198 202 196 205 169 112 149 215 194 #> Q  91  43  46  61 154   0  29  87  24 109 113  53 101 116  76  68  42 130  99 #> E 107  54  42  45 170  29   0  98  40 134 138  56 126 140  93  80  65 152 122 #> G  60 125  80  94 159  87  98   0  98 135 138 127 127 153  42  56  59 184 147 #> H  86  29  68  81 174  24  40  98   0  94  99  32  87 100  77  89  47 115  83 #> I  94  97 149 168 198 109 134 135  94   0   5 102  10  21  95 142  89  61  33 #> L  96 102 153 172 198 113 138 138  99   5   0 107  15  22  98 145  92  61  36 #> K 106  26  94 101 202  53  56 127  32 102 107   0  95 102 103 121  78 110  85 #> M  84  91 142 160 196 101 126 127  87  10  15  95   0  28  87 135  81  67  36 #> F 113  97 158 177 205 116 140 153 100  21  22 102  28   0 114 155 103  40  22 #> P  27 103  91 108 169  76  93  42  77  95  98 103  87 114   0  74  38 147 110 #> S  99 110  46  65 112  68  80  56  89 142 145 121 135 155  74   0  58 177 144 #> T  58  71  65  85 149  42  65  59  47  89  92  78  81 103  38  58   0 128  92 #> W 148 101 174 181 215 130 152 184 115  61  61 110  67  40 147 177 128   0  37 #> Y 112  77 143 160 194  99 122 147  83  33  36  85  36  22 110 144  92  37   0 #> V  64  96 133 152 192  96 121 109  84  29  32  97  21  50  68 124  69  88  55 #>     V #> A  64 #> R  96 #> N 133 #> D 152 #> C 192 #> Q  96 #> E 121 #> G 109 #> H  84 #> I  29 #> L  32 #> K  97 #> M  21 #> F  50 #> P  68 #> S 124 #> T  69 #> W  88 #> Y  55 #> V   0  # All ones, and zeros on the diagonal amino_distance_matrix(\"uniform\") #>   A R N D C Q E G H I L K M F P S T W Y V #> A 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> R 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> N 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> D 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> C 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> Q 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> E 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 #> G 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 #> H 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 #> I 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 #> L 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 #> K 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 #> M 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 #> F 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 #> P 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 #> S 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 #> T 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 #> W 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 #> Y 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 #> V 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0"},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"genotype name, return dosage matrix residue (amino acid nucleotide) position.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"","code":"dosage(   mat,   names,   drop_constants = TRUE,   drop_duplicates = FALSE,   verbose = FALSE )"},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"mat one-hot encoded matrix one row per allele one column residue (amino acid nucleotide) position. names Input character vector one genotype individual. entries must present rownames(mat). drop_constants Filter constant amino acid positions. TRUE default. drop_duplicates Filter duplicate amino acid positions. FALSE default. verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"matrix one row input genotype, one column residue position.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"genotype represented like \"HLA-*01:01,HLA-*01:01\" default, returned matrix filtered exclude: positions input genotypes allele","code":""},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"","code":"DRB1_file <- file.path(   \"https://github.com/ANHIG/IMGTHLA/raw\",   \"5f2c562056f8ffa89aeea0631f2a52300ee0de17\",   \"alignments/DRB1_prot.txt\" ) a <- read_alignments(DRB1_file) genotypes <- c(   \"DRB1*12:02:02:03,DRB1*12:02:02:03,DRB1*14:54:02\",   \"DRB1*04:174,DRB1*15:152\",   \"DRB1*04:56:02,DRB1*15:01:48\",   \"DRB1*14:172,DRB1*04:160\",   \"DRB1*04:359,DRB1*04:284:02\" ) dosage <- dosage(a$onehot, genotypes) dosage[,1:5] #>                                                 n29unk Mn29 n28unk Vn28 n27unk #> DRB1*12:02:02:03,DRB1*12:02:02:03,DRB1*14:54:02      1    2      1    2      1 #> DRB1*04:174,DRB1*15:152                              2    0      2    0      2 #> DRB1*04:56:02,DRB1*15:01:48                          2    0      2    0      2 #> DRB1*14:172,DRB1*04:160                              2    0      2    0      2 #> DRB1*04:359,DRB1*04:284:02                           2    0      2    0      2"},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"function : Get folder name getOption(\"hlabud_dir\") else automatically choose appropriate folder operating system thanks rappdirs. Create folder automatically already exist. Set hlabud_dir option new folder.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"","code":"get_hlabud_dir()"},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"name folder.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"locations hlabud_dir folder operating system. Linux:   Mac:   Windows:   set hlabud_dir option, please use:","code":"~/.local/share/hlabud ~/Library/Application Support/hlabud C:\\Documents and Settings\\{User}\\Application Data\\slowkow\\hlabud options(hlabud_dir = \"/my/favorite/path\")"},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"","code":"if (FALSE) { hlabud_dir <- get_hlabud_dir() }"},{"path":"https://slowkow.github.io/hlabud/reference/get_onehot.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a one-hot encoded matrix from a dataframe of amino acid sequences. — get_onehot","title":"Make a one-hot encoded matrix from a dataframe of amino acid sequences. — get_onehot","text":"Make one-hot encoded matrix dataframe amino acid sequences.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/get_onehot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a one-hot encoded matrix from a dataframe of amino acid sequences. — get_onehot","text":"","code":"get_onehot(sequences, n_pre, verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/get_onehot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a one-hot encoded matrix from a dataframe of amino acid sequences. — get_onehot","text":"n_pre number amino acid sequences position 1. verbose Print messages along way. al dataframe columns allele, seq","code":""},{"path":"https://slowkow.github.io/hlabud/reference/grantham.html","id":null,"dir":"Reference","previous_headings":"","what":"Table 1 from Grantham 1974 — grantham","title":"Table 1 from Grantham 1974 — grantham","text":"Grantham R. Amino Acid Difference Formula Help Explain Protein Evolution. Science. 1974;185: 862–864. doi:10.1126/science.185.4154.862","code":""},{"path":"https://slowkow.github.io/hlabud/reference/grantham.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Table 1 from Grantham 1974 — grantham","text":"","code":"grantham"},{"path":"https://slowkow.github.io/hlabud/reference/grantham.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Table 1 from Grantham 1974 — grantham","text":"data frame 20 rows 5 columns: amino Amino acid c Composition c, atomic weight ratio noncarbon elements end groups rings carbons side chain p Polarity p published data v Volume v published data","code":""},{"path":"https://slowkow.github.io/hlabud/reference/grantham.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Table 1 from Grantham 1974 — grantham","text":"","code":"grantham #>    amino    c    p     v #> 1    Ser 1.42  9.2  32.0 #> 2    Arg 0.65 10.5 124.0 #> 3    Leu 0.00  4.9 111.0 #> 4    Pro 0.39  8.0  32.5 #> 5    Thr 0.71  8.6  61.0 #> 6    Ala 0.00  8.1  31.0 #> 7    Val 0.00  5.9  84.0 #> 8    Gly 0.74  9.0   3.0 #> 9    Ile 0.00  5.2 111.0 #> 10   Phe 0.00  5.2 132.0 #> 11   Tyr 0.20  6.2 136.0 #> 12   Cys 2.75  5.5  55.0 #> 13   His 0.58 10.4  96.0 #> 14   Gln 0.89 10.5  85.0 #> 15   Asn 1.33 11.6  56.0 #> 16   Lys 0.33 11.3 119.0 #> 17   Asp 1.38 13.0  54.0 #> 18   Glu 0.92 12.3  83.0 #> 19   Met 0.00  5.7 105.0 #> 20   Trp 0.13  5.4 170.0"},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":null,"dir":"Reference","previous_headings":"","what":"Get sequence alignments from IMGTHLA — hla_alignments","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"conventions used alignments (EBI IMGT-HLA help page): entry allele displayed respect reference sequences. identity reference sequence present base displayed hyphen (-). Non-identity reference sequence shown displaying appropriate base position. insertion deletion occurred represented period (.). sequence unknown point alignment, represented asterisk (*). protein alignments null alleles, 'Stop' codons represented hash (X). protein alignments, sequence following termination codon, marked appear blank. conventions used nucleotide protein alignments.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"","code":"hla_alignments(   gene = \"DRB1\",   type = \"prot\",   release = \"latest\",   verbose = FALSE )"},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"gene name gene like \"DRB1\" type type sequence, one \"prot\", \"nuc\", \"gen\" release Default \"latest\". release name like \"3.51.0\". verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"list character vector called sequences two matrices called alleles onehot. character vector sequences one sequence allele, names allele names. matrix alleles one row allele, one column position, values representing residues position allele. matrix onehot one-hot encoding variants distinguish alleles, one row allele one column amino acid position.","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"","code":"# \\donttest{ a <- hla_alignments(\"DRB1\") head(a$sequences) #>                                                                                                                                                                                                                                                                DRB1*01:01:01:01  #> \"MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGTERVR.LLERCIYNQEE.SVRFDSDVGEYRAVTELGRPDAEYWNSQKDLLEQRRAAVDTYCRHNYGVGESFTVQRR.VEPKVTVYPSKTQPLQHHNLLVCSVSGFYPGSIEVRWFRNGQEEKAGVVSTGLIQNGDWTFQTLVMLETVPRSGEVYTCQVEHPSVTSPLTVEWRARSESAQSKMLSGVGGFVLGLLFLGAGLFIYFRNQKGHSGLQPTGFLS\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:02  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:03  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:04  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:05  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:06  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  a$alleles[1:6,1:6] #>                  n29 n28 n27 n26 n25 n24 #> DRB1*01:01:01:01 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:02 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:03 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:04 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:05 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:06 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" a$onehot[1:6,1:6] #>                  n29unk Mn29 n28unk Ln28 Vn28 n27unk #> DRB1*01:01:01:01      0    1      0    0    1      0 #> DRB1*01:01:01:02      0    1      0    0    1      0 #> DRB1*01:01:01:03      0    1      0    0    1      0 #> DRB1*01:01:01:04      0    1      0    0    1      0 #> DRB1*01:01:01:05      0    1      0    0    1      0 #> DRB1*01:01:01:06      0    1      0    0    1      0 # }"},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"Download list allele names HLA genes particular IMGTHLA release.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"","code":"hla_alleles(release = \"latest\", overwrite = FALSE, verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"release Default \"latest\". release name like \"3.51.0\". overwrite Overwrite existing alleles.json file Allelelist.{version}.txt file verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"data frame HLA allele ids names","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"","code":"# \\donttest{ head(hla_alleles()) #>   AlleleID         Allele #> 1 HLA00001  A*01:01:01:01 #> 2 HLA02169 A*01:01:01:02N #> 3 HLA14798  A*01:01:01:03 #> 4 HLA15760  A*01:01:01:04 #> 5 HLA16415  A*01:01:01:05 #> 6 HLA16417  A*01:01:01:06 # }"},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate HLA divergence for each individual — hla_divergence","title":"Calculate HLA divergence for each individual — hla_divergence","text":"First, convert allele name (e.g. *01:01) amino acid sequence. divergence sum distances pair amino acids position, divided total sequence length. amino acid distance matrix use one published Grantham 1974 (doi:10.1126/science.185.4154.862), based three physical properties amino acids (composition, polarity, molecular volume) correlated estimate relative substitution frequency.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate HLA divergence for each individual — hla_divergence","text":"","code":"hla_divergence(   alleles = c(\"A*01:01,A*02:01\"),   method = \"grantham\",   release = \"latest\",   verbose = FALSE )"},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate HLA divergence for each individual — hla_divergence","text":"alleles character vector comma-delimited alleles individual. usually expect two alleles per individual, possible (fewer) copies due copy number alterations. function still works individual different number alleles. method pairwise amino acid matrix, method name: \"grantham\" \"uniform\" indicate pairwise amino acid distance matrix use. choose pass matrix, 20x20 symmetric matrix zeros diagonal, rownames colnames one-letter amino acid codes R N D C Q E G H L K M F P S T W Y V. release Default \"latest\". release name like \"3.51.0\". verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate HLA divergence for each individual — hla_divergence","text":"dataframe divergence individual.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate HLA divergence for each individual — hla_divergence","text":"code function translation original Perl code Tobias Lenz, published Pierini & Lenz 2018 MolBiolEvol (https://doi.org/10.1093/molbev/msy116). comparing two amino acid sequences, characters one 20 amino acids considered divergence calculation, gaps (characters) count.","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate HLA divergence for each individual — hla_divergence","text":"","code":"my_genos <- c(\"A*23:01:12,A*24:550\", \"A*25:12N,A*11:27\",               \"A*24:381,A*33:85\", \"A*01:01:,A*01:01,A*02:01\") hla_divergence(my_genos, method = \"grantham\") #>      A*23:01:12,A*24:550         A*25:12N,A*11:27         A*24:381,A*33:85  #>                0.5131579                3.4736842                5.1078947  #> A*01:01:,A*01:01,A*02:01  #>                3.9982456   # This is equivalent hla_divergence(my_genos, method = amino_distance_matrix(\"grantham\")) #>      A*23:01:12,A*24:550         A*25:12N,A*11:27         A*24:381,A*33:85  #>                0.5131579                3.4736842                5.1078947  #> A*01:01:,A*01:01,A*02:01  #>                3.9982456"},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":null,"dir":"Reference","previous_headings":"","what":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"Download read table HLA allele frequencies Allele Frequency Net Database (AFND).","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"","code":"hla_frequencies(verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"dataframe HLA allele frequencies genes.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"use data, please cite latest manuscript Allele Frequency Net Database: Gonzalez-Galarza FF, McCabe , Santos EJMD, Jones J, Takeshita L, Ortega-Rivera ND, et al. Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data new query tools. Nucleic Acids Res. 2020;48: D783–D788. doi:10.1093/nar/gkz1029","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"","code":"# \\donttest{ hla_frequencies() #> # A tibble: 123,502 × 7 #>    group gene  allele  population            indivs_over_n alleles_over_2n     n #>                                               #>  1 hla   A     A*01:01 Argentina Rosario To…          15.1           0.076    86 #>  2 hla   A     A*01:01 Armenia combined Reg…          NA             0.125   100 #>  3 hla   A     A*01:01 Australia Cape York …          NA             0.053   103 #>  4 hla   A     A*01:01 Australia Groote Eyl…          NA             0.027    75 #>  5 hla   A     A*01:01 Australia New South …          NA             0.187   134 #>  6 hla   A     A*01:01 Australia Yuendumu A…          NA             0.008   191 #>  7 hla   A     A*01:01 Austria                        27             0.146   200 #>  8 hla   A     A*01:01 Azores Central Islan…          NA             0.08     59 #>  9 hla   A     A*01:01 Azores Oriental Isla…          NA             0.115    43 #> 10 hla   A     A*01:01 Azores Terceira Isla…          NA             0.109   130 #> # ℹ 123,492 more rows # }"},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Get HLA gene names from IMGTHLA — hla_genes","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"Retrieve list txt files github.com/ANHIG/IMGTHLA/alignments return list gene names derived file names.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"","code":"hla_genes(release = \"latest\", overwrite = FALSE, verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"release Default \"latest\". release name like \"3.51.0\". overwrite Overwrite existing genes.json file new one GitHub verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"tibble two columns: HLA gene names (\"\", \"DRB1\") types (\"nuc\", \"gen\", \"prot\").","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"","code":"# \\donttest{ hla_genes()  #> # A tibble: 107 × 2 #>    gene  type  #>      #>  1 A     gen   #>  2 A     nuc   #>  3 A     prot  #>  4 B     gen   #>  5 B     nuc   #>  6 B     prot  #>  7 C     gen   #>  8 C     nuc   #>  9 C     prot  #> 10 DMA   gen   #> # ℹ 97 more rows # }"},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the names of releases from IMGTHLA — hla_releases","title":"Get the names of releases from IMGTHLA — hla_releases","text":"Get tags github.com/ANHIG/IMGTHLA, save file called tags.json getOption(\"hlabud_dir\"),  return release names file.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the names of releases from IMGTHLA — hla_releases","text":"","code":"hla_releases(overwrite = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the names of releases from IMGTHLA — hla_releases","text":"overwrite Overwrite existing tags.json file getOption(\"hlabud_dir\")","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the names of releases from IMGTHLA — hla_releases","text":"character vector release names like \"3.51.0\"","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the names of releases from IMGTHLA — hla_releases","text":"tags.json file automatically overwritten older 24 hours.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the names of releases from IMGTHLA — hla_releases","text":"","code":"# \\donttest{ hla_releases()  #>  [1] \"3.56.0\"   \"3.55.0\"   \"3.54.0\"   \"3.53.0\"   \"3.52.0\"   \"3.51.0\"   #>  [7] \"3.50.0\"   \"3.49.0\"   \"3.48.0\"   \"3.47.0\"   \"3.46.0\"   \"3.45.1\"   #> [13] \"3.45.01\"  \"3.45.0.1\" \"3.45.0\"   \"3.44.1\"   \"3.44.0\"   \"3.43.0\"   #> [19] \"3.42.0\"   \"3.41.2\"   \"3.41.0\"   \"3.40.0\"   \"3.39.0\"   \"3.38.0\"   #> [25] \"3.37.0\"   \"3.36.0\"   \"3.35.0\"   \"3.34.0\"   \"3.33.0\"   \"3.32.0\"   # }"},{"path":"https://slowkow.github.io/hlabud/reference/hlabud-package.html","id":null,"dir":"Reference","previous_headings":"","what":"hlabud: Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA — hlabud-package","title":"hlabud: Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA — hlabud-package","text":"Fetch sequence alignment data IMGTHLA database Robinson et al (2020) doi:10.1093/nar/gkz950 , automatically convert sequence alignments convenient R matrices ready downstream analysis. vignette shows examples using one-hot encoding data logistic regression dimensionality reduction. Data downloaded lazily, -needed, cached user-configurable folder.","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hlabud-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"hlabud: Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA — hlabud-package","text":"Maintainer: Kamil Slowikowski kslowikowski@gmail.com (ORCID)","code":""},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and unpack a tarball release from IMGTHLA — install_hla","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"release tarball Github unpacked getOption(\"hlabud_dir\") folder.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"","code":"install_hla(release = \"latest\", overwrite = FALSE, verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"release Default \"latest\". release name like \"3.51.0\". overwrite TRUE, overwrite existing files release folder. verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"Note latest releases 100 MB size, download might take slow connections.","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"","code":"if (FALSE) { install_hla() install_hla(\"3.51.0\") install_hla(\"3.51.0\", verbose = TRUE) # Change the install directory options(hlabud_dir = \"path/to/my/dir\") install_hla() }"},{"path":"https://slowkow.github.io/hlabud/reference/one_to_three.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert one letter amino acid codes to three letter amino acid codes — one_to_three","title":"Convert one letter amino acid codes to three letter amino acid codes — one_to_three","text":"Convert one letter amino acid codes three letter amino acid codes","code":""},{"path":"https://slowkow.github.io/hlabud/reference/one_to_three.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert one letter amino acid codes to three letter amino acid codes — one_to_three","text":"","code":"one_to_three(aminos)"},{"path":"https://slowkow.github.io/hlabud/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":null,"dir":"Reference","previous_headings":"","what":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"function reads txt files provided IMGTHLA.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"","code":"read_alignments(file)"},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"file File name txt file IMGTHLA like \"DQB1_prot.txt\"","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"list character vector called sequences two matrices alleles onehot. matrix alleles one row allele, one column position, values representing residues position allele. matrix onehot one-hot encoding variants distinguish alleles, one row allele one column amino acid position.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"Consider using hla_alignments() instead function. already txt file want read, can read read_alignments(\"myfile.txt\"). sequences contained file: {gene}_prot.txt amino acid sequence HLA allele. {gene}_nuc.txt nucleotide sequence exons. {gene}_gen.txt genomic sequence exons introns.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"","code":"my_file <- file.path(   \"https://github.com/ANHIG/IMGTHLA/raw\",   \"5f2c562056f8ffa89aeea0631f2a52300ee0de17\",   \"alignments/DRB1_prot.txt\" ) a <- read_alignments(my_file) head(a$sequences) #>                                                                                                                                                                                                                                                                DRB1*01:01:01:01  #> \"MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGTERVR.LLERCIYNQEE.SVRFDSDVGEYRAVTELGRPDAEYWNSQKDLLEQRRAAVDTYCRHNYGVGESFTVQRR.VEPKVTVYPSKTQPLQHHNLLVCSVSGFYPGSIEVRWFRNGQEEKAGVVSTGLIQNGDWTFQTLVMLETVPRSGEVYTCQVEHPSVTSPLTVEWRARSESAQSKMLSGVGGFVLGLLFLGAGLFIYFRNQKGHSGLQPTGFLS\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:02  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:03  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:04  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:05  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:06  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  a$alleles[1:5,1:5] #>                  n29 n28 n27 n26 n25 #> DRB1*01:01:01:01 \"M\" \"V\" \"C\" \"L\" \"K\" #> DRB1*01:01:01:02 \"M\" \"V\" \"C\" \"L\" \"K\" #> DRB1*01:01:01:03 \"M\" \"V\" \"C\" \"L\" \"K\" #> DRB1*01:01:01:04 \"M\" \"V\" \"C\" \"L\" \"K\" #> DRB1*01:01:01:05 \"M\" \"V\" \"C\" \"L\" \"K\" a$onehot[1:5,1:5] #>                  n29unk Mn29 n28unk Vn28 n27unk #> DRB1*01:01:01:01      0    1      0    1      0 #> DRB1*01:01:01:02      0    1      0    1      0 #> DRB1*01:01:01:03      0    1      0    1      0 #> DRB1*01:01:01:04      0    1      0    1      0 #> DRB1*01:01:01:05      0    1      0    1      0"},{"path":[]},{"path":"https://slowkow.github.io/hlabud/news/index.html","id":"bug-fixes-2-0-0","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"hlabud 2.0.0","text":"Fix incorrect position numbering, accounting insertions deletions indicated “.” character. Thanks Vinicius Stelet bringing attention issue #3. Instead discarding positions *, include label unk, example pos241_unk indicates unknown amino acid position 241. Thanks Sreekar Mantena reporting issue! Fix --one error. example, HLA-pos361_- colnames($onehot) reference allele instead -. now fixed. Thanks Sreekar Mantena reporting issue!","code":""},{"path":"https://slowkow.github.io/hlabud/news/index.html","id":"changes-2-0-0","dir":"Changelog","previous_headings":"","what":"Changes","title":"hlabud 2.0.0","text":"Change position names pos21_D D21. negative, posn21_D Dn21. Change dosage() take one-hot matrix first argument. Change dosage() return full allele names IMGT matching partial allele names like DRB1*03 DRB1*03:01. show messages indicating alleles matched verbose=TRUE. Automatically overwrite {hlabud_dir}/alleles.json older 24 hours. Automatically overwrite {hlabud_dir}/tags.json older 24 hours.","code":""},{"path":"https://slowkow.github.io/hlabud/news/index.html","id":"hlabud-100","dir":"Changelog","previous_headings":"","what":"hlabud 1.0.0","title":"hlabud 1.0.0","text":"Initial release. Added NEWS.md file track changes package.","code":""}]
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This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.  You should have received a copy of the GNU General Public License along with this program.  If not, see .   Copyright (C)    This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"hlabud usage examples","text":"Kamil Slowikowski 2024-06-05 hlabud R package provides functions facilitate download analysis human leukocyte antigen (HLA) genotype sequence alignments IMGTHLA R. Let’s consider question might want answer HLA genotypes. amino acid positions different two genotypes? nucleotides different?","code":"library(hlabud) a <- hla_alignments(\"DRB1\") a$release #> [1] \"3.56.0\" dosage(a$onehot, c(\"DRB1*03:01:05\", \"DRB1*03:02:03\")) #>               F26 Y26 D28 E28 F47 Y47 G86 V86 #> DRB1*03:01:05   0   1   1   0   1   0   0   1 #> DRB1*03:02:03   1   0   0   1   0   1   1   0 n <- hla_alignments(\"DRB1\", type = \"nuc\") n$release #> [1] \"3.56.0\" dosage(n$onehot, c(\"DRB1*03:01:05\", \"DRB1*03:02:03\")) #>               A164 T164 C171 G171 A227 T227 A240 G240 G344 T344 G345 T345 A357 #> DRB1*03:01:05    1    0    1    0    0    1    1    0    0    1    1    0    1 #> DRB1*03:02:03    0    1    0    1    1    0    0    1    1    0    0    1    0 #>               G357 #> DRB1*03:01:05    0 #> DRB1*03:02:03    1"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"installation","dir":"Articles","previous_headings":"","what":"Installation","title":"hlabud usage examples","text":"quickest way get hlabud install GitHub: , included usage examples. hope inspire share HLA analyses. source code page available . Thank reporting issues hlabud.","code":"# install.packages(\"devtools\") devtools::install_github(\"slowkow/hlabud\")"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"get-a-one-hot-encoded-matrix-for-all-hla-drb1-alleles","dir":"Articles","previous_headings":"","what":"Get a one-hot encoded matrix for all HLA-DRB1 alleles","title":"hlabud usage examples","text":"can use hla_alignments(\"DRB1\") load DRB1_prot.txt file latest IMGTHLA release: object list three items: $sequences amino acid sequence alignments named character vector: conventions used alignments (copied EBI help page): entry allele displayed respect reference sequences. identity reference sequence present base displayed hyphen (-). Non-identity reference sequence shown displaying appropriate base position. insertion deletion occurred represented period (.). sequence unknown point alignment, represented asterisk (*). protein alignments null alleles, ‘Stop’ codons represented hash (X). protein alignments, sequence following termination codon, marked appear blank. conventions used nucleotide protein alignments. $alleles matrix amino acids one column position: $onehot one-hot encoded matrix one column amino acid position: one-hot encoded matrix? simple example demonstrate idea:","code":"library(hlabud) a <- hla_alignments(gene = \"DRB1\", verbose = TRUE) #> Reading /home/runner/.local/share/hlabud/3.56.0/alignments/DRB1_prot.txt str(a) #> List of 7 #>  $ sequences: Named chr [1:3671] \"MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGTERVR.LLERCIYNQEE.SVRFDSDVGEYRAVTELGRPDAEYWNSQKDLLEQRRAAVDTYCR\"| __truncated__ \"------------------------------------------------------.-----------.--------------------------------------------\"| __truncated__ \"------------------------------------------------------.-----------.--------------------------------------------\"| __truncated__ \"------------------------------------------------------.-----------.--------------------------------------------\"| __truncated__ ... #>   ..- attr(*, \"names\")= chr [1:3671] \"DRB1*01:01:01:01\" \"DRB1*01:01:01:02\" \"DRB1*01:01:01:03\" \"DRB1*01:01:01:04\" ... #>  $ alleles  : chr [1:3671, 1:288] \"M\" \"M\" \"M\" \"M\" ... #>   ..- attr(*, \"dimnames\")=List of 2 #>   .. ..$ : chr [1:3671] \"DRB1*01:01:01:01\" \"DRB1*01:01:01:02\" \"DRB1*01:01:01:03\" \"DRB1*01:01:01:04\" ... #>   .. ..$ : chr [1:288] \"n29\" \"n28\" \"n27\" \"n26\" ... #>  $ onehot   : num [1:3671, 1:1658] 0 0 0 0 0 0 0 0 0 0 ... #>   ..- attr(*, \"dimnames\")=List of 2 #>   .. ..$ : chr [1:3671] \"DRB1*01:01:01:01\" \"DRB1*01:01:01:02\" \"DRB1*01:01:01:03\" \"DRB1*01:01:01:04\" ... #>   .. ..$ : chr [1:1658] \"n29unk\" \"Mn29\" \"n28unk\" \"Ln28\" ... #>  $ gene     : chr \"DRB1\" #>  $ type     : chr \"prot\" #>  $ release  : chr \"3.56.0\" #>  $ file     : chr \"/home/runner/.local/share/hlabud/3.56.0/alignments/DRB1_prot.txt\" substr(head(a$sequences, 6), 1, 50) #>                                     DRB1*01:01:01:01  #> \"MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGT\"  #>                                     DRB1*01:01:01:02  #> \"--------------------------------------------------\"  #>                                     DRB1*01:01:01:03  #> \"--------------------------------------------------\"  #>                                     DRB1*01:01:01:04  #> \"--------------------------------------------------\"  #>                                     DRB1*01:01:01:05  #> \"--------------------------------------------------\"  #>                                     DRB1*01:01:01:06  #> \"--------------------------------------------------\" a$alleles[1:5,1:40] #>                  n29 n28 n27 n26 n25 n24 n23 n22 n21 n20 n19 n18 n17 n16 n15 #> DRB1*01:01:01:01 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #> DRB1*01:01:01:02 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #> DRB1*01:01:01:03 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #> DRB1*01:01:01:04 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #> DRB1*01:01:01:05 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" \"P\" \"G\" \"G\" \"S\" \"C\" \"M\" \"T\" \"A\" \"L\" #>                  n14 n13 n12 n11 n10 n9  n8  n7  n6  n5  n4  n3  n2  n1  1   #> DRB1*01:01:01:01 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #> DRB1*01:01:01:02 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #> DRB1*01:01:01:03 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #> DRB1*01:01:01:04 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #> DRB1*01:01:01:05 \"T\" \"V\" \"T\" \"L\" \"M\" \"V\" \"L\" \"S\" \"S\" \"P\" \"L\" \"A\" \"L\" \"A\" \"G\" #>                  2   3   4   5   6   7   8   9   10  11  #> DRB1*01:01:01:01 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" #> DRB1*01:01:01:02 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" #> DRB1*01:01:01:03 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" #> DRB1*01:01:01:04 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" #> DRB1*01:01:01:05 \"D\" \"T\" \"R\" \"P\" \"R\" \"F\" \"L\" \"W\" \"Q\" \"L\" a$onehot[1:5,1:25] #>                  n29unk Mn29 n28unk Ln28 Vn28 n27unk Cn27 n26unk Ln26 n25unk #> DRB1*01:01:01:01      0    1      0    0    1      0    1      0    1      0 #> DRB1*01:01:01:02      0    1      0    0    1      0    1      0    1      0 #> DRB1*01:01:01:03      0    1      0    0    1      0    1      0    1      0 #> DRB1*01:01:01:04      0    1      0    0    1      0    1      0    1      0 #> DRB1*01:01:01:05      0    1      0    0    1      0    1      0    1      0 #>                  Kn25 Rn25 n24unk Fn24 Ln24 n23unk Pn23 n22unk Gn22 n21unk Cn21 #> DRB1*01:01:01:01    1    0      0    0    1      0    1      0    1      0    0 #> DRB1*01:01:01:02    1    0      0    0    1      0    1      0    1      0    0 #> DRB1*01:01:01:03    1    0      0    0    1      0    1      0    1      0    0 #> DRB1*01:01:01:04    1    0      0    0    1      0    1      0    1      0    0 #> DRB1*01:01:01:05    1    0      0    0    1      0    1      0    1      0    0 #>                  Gn21 n20unk Sn20 n19unk #> DRB1*01:01:01:01    1      0    1      0 #> DRB1*01:01:01:02    1      0    1      0 #> DRB1*01:01:01:03    1      0    1      0 #> DRB1*01:01:01:04    1      0    1      0 #> DRB1*01:01:01:05    1      0    1      0 dat <- data.frame(   V1 = c(\"A\", \"A\", \"B\"),   V2 = c(\"B\", \"B\", \"B\"),   V3 = c(\"C\", \"B\", \"B\"),   stringsAsFactors = TRUE ) dat #>   V1 V2 V3 #> 1  A  B  C #> 2  A  B  B #> 3  B  B  B predict(onehot::onehot(dat), dat) #>      V1=A V1=B V2=B V3=B V3=C #> [1,]    1    0    1    0    1 #> [2,]    1    0    1    1    0 #> [3,]    0    1    1    1    0"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"convert-genotypes-to-a-dosage-matrix","dir":"Articles","previous_headings":"","what":"Convert genotypes to a dosage matrix","title":"hlabud usage examples","text":"Suppose individuals following genotypes: want run association test amino acid positions, need convert genotype names matrix allele dosages (e.g., 0, 1, 2). can use dosage() convert individual’s genotypes amino acid dosages: Note: dosage matrix one row individual one column amino acid position. default, dosage() discard columns individuals identical. input allele names truncated 4-digits 2-digits (e.g. DRB1*03:01 DRB1*03), hlabud pick first allele matches input allele (e.g. DRB1*03:01:01:01). want specific allele, need provide full allele name input. Please careful check data looks way expect!","code":"genotypes <- c(   \"DRB1*12:02:02:03,DRB1*12:02:02:03\",   \"DRB1*04:174,DRB1*15:152\",   \"DRB1*04:56:02,DRB1*15:01:48\",   \"DRB1*14:172,DRB1*04:160\",   \"DRB1*04:359,DRB1*04:284:02\" ) dosage <- dosage(a$onehot, genotypes) dosage[,1:8] #>                                   n29unk Mn29 n28unk Vn28 n27unk Cn27 n26unk #> DRB1*12:02:02:03,DRB1*12:02:02:03      0    2      0    2      0    2      0 #> DRB1*04:174,DRB1*15:152                2    0      2    0      2    0      2 #> DRB1*04:56:02,DRB1*15:01:48            2    0      2    0      2    0      2 #> DRB1*14:172,DRB1*04:160                2    0      2    0      2    0      2 #> DRB1*04:359,DRB1*04:284:02             2    0      2    0      2    0      2 #>                                   Ln26 #> DRB1*12:02:02:03,DRB1*12:02:02:03    2 #> DRB1*04:174,DRB1*15:152              0 #> DRB1*04:56:02,DRB1*15:01:48          0 #> DRB1*14:172,DRB1*04:160              0 #> DRB1*04:359,DRB1*04:284:02           0 dim(dosage) #> [1]   5 428"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"logistic-regression-association-for-amino-acid-positions","dir":"Articles","previous_headings":"","what":"Logistic regression association for amino acid positions","title":"hlabud usage examples","text":"Let’s simulate dataset cases controls demonstrate one approach testing amino acid positions might associated cases. simulated dataset 100 individuals, 52 cases 48 controls. also one column amino acid position might want test association case variable. One possible approach association testing use glm() fit logistic regression model amino acid position. reveal amino acid position might associated case variable simulated dataset. volcano shows Odds Ratio P-value amino acid position. top hits P < 0.05 labeled.  simulation, case variable associated F37 (P = 0.021, = 4, 95% CI 1.4 15).","code":"set.seed(2) n <- 100 d <- data.frame(   geno = paste(     sample(rownames(a$onehot), n, replace = TRUE),     sample(rownames(a$onehot), n, replace = TRUE),     sep = \",\"   ),   age = sample(21:100, n, replace = TRUE),   case = sample(0:1, n, replace = TRUE) ) d <- cbind(d, dosage(a$onehot, d$geno)) d[1:5,1:6] #>                                                          geno age case n29unk #> DRB1*04:243,DRB1*15:01:01:08     DRB1*04:243,DRB1*15:01:01:08  67    0      1 #> DRB1*04:08:01:01,DRB1*04:56:02 DRB1*04:08:01:01,DRB1*04:56:02  38    1      1 #> DRB1*13:339,DRB1*04:112               DRB1*13:339,DRB1*04:112  67    0      2 #> DRB1*03:85,DRB1*01:02:10             DRB1*03:85,DRB1*01:02:10  55    0      2 #> DRB1*03:62,DRB1*14:224                 DRB1*03:62,DRB1*14:224  73    1      1 #>                                Mn29 n28unk #> DRB1*04:243,DRB1*15:01:01:08      1      1 #> DRB1*04:08:01:01,DRB1*04:56:02    1      1 #> DRB1*13:339,DRB1*04:112           0      2 #> DRB1*03:85,DRB1*01:02:10          0      2 #> DRB1*03:62,DRB1*14:224            1      1 # prepare column names for use in formulas ix <- 4:ncol(d) colnames(d)[ix] <- sprintf(\"VAR%s\", colnames(d)[ix])  # select the amino acid positions that have at least 3 people with dosage > 0 my_as <- names(which(colSums(d[,4:ncol(d)] > 0) >= 3))  # run the association tests my_glm <- rbindlist(pblapply(my_as, function(my_a) {   f <- sprintf(\"case ~ %s\", my_a)   glm(as.formula(f), data = d, family = \"binomial\") %>%     parameters(exponentiate = TRUE) }))  # look at the top hits my_glm %>%   arrange(p) %>%   filter(!Parameter %in% c(\"(Intercept)\")) %>%   head #>    Parameter Coefficient        SE    CI     CI_low    CI_high         z #>                                      #> 1:    VARF37   3.9529448 2.3501312  0.95 1.35121582 14.6317263  2.311857 #> 2:    VARY60   0.4269585 0.1790904  0.95 0.18053396  0.9458131 -2.028981 #> 3:    VARK98   0.5739907 0.1603272  0.95 0.32635370  0.9824460 -1.987475 #> 4:   VARS104   0.5739907 0.1603272  0.95 0.32635370  0.9824460 -1.987475 #> 5:    VARQ96   0.3253919 0.1886793  0.95 0.08932709  0.9191775 -1.936226 #> 6:   VARS179   0.6085247 0.1617164  0.95 0.35644231  1.0163414 -1.869106 #>    df_error          p #>              #> 1:      Inf 0.02078556 #> 2:      Inf 0.04246025 #> 3:      Inf 0.04686976 #> 4:      Inf 0.04686976 #> 5:      Inf 0.05284007 #> 6:      Inf 0.06160809"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"umap-embedding-of-hla-drb1-alleles","dir":"Articles","previous_headings":"","what":"UMAP embedding of HLA-DRB1 alleles","title":"hlabud usage examples","text":"many possibilities analysis one-hot encoding matrix. example, UMAP embedding HLA-DRB1 alleles encoded one-hot amino acid matrix 1658 columns, one amino acid position. color indicates 2-digit allele name.  can highlight alleles aspartic acid (Asp D) position 57:  can use color represent amino acid residue position 57:","code":"uamp(a$onehot, n_epochs = 200, min_dist = 1, spread = 2)"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"get-hla-allele-frequencies-from-allele-frequency-net-database-afnd","dir":"Articles","previous_headings":"","what":"Get HLA allele frequencies from Allele Frequency Net Database (AFND)","title":"hlabud usage examples","text":"hlabud R package includes table HLA allele frequencies Allele Frequency Net Database (AFND). use data, please cite latest manuscript Allele Frequency Net Database: Gonzalez-Galarza FF, McCabe , Santos EJMD, Jones J, Takeshita L, Ortega-Rivera ND, et al. Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data new query tools. Nucleic Acids Res. 2020;48: D783–D788. doi:10.1093/nar/gkz1029 can use data plot frequency specific allele (e.g. DQB1*02:01) populations 1000 sampled individuals:  See github.com/slowkow/allelefrequencies examples might use data.","code":"af <- hla_frequencies() af #> # A tibble: 123,502 × 7 #>    group gene  allele  population            indivs_over_n alleles_over_2n     n #>                                               #>  1 hla   A     A*01:01 Argentina Rosario To…          15.1           0.076    86 #>  2 hla   A     A*01:01 Armenia combined Reg…          NA             0.125   100 #>  3 hla   A     A*01:01 Australia Cape York …          NA             0.053   103 #>  4 hla   A     A*01:01 Australia Groote Eyl…          NA             0.027    75 #>  5 hla   A     A*01:01 Australia New South …          NA             0.187   134 #>  6 hla   A     A*01:01 Australia Yuendumu A…          NA             0.008   191 #>  7 hla   A     A*01:01 Austria                        27             0.146   200 #>  8 hla   A     A*01:01 Azores Central Islan…          NA             0.08     59 #>  9 hla   A     A*01:01 Azores Oriental Isla…          NA             0.115    43 #> 10 hla   A     A*01:01 Azores Terceira Isla…          NA             0.109   130 #> # ℹ 123,492 more rows my_allele <- \"DQB1*02:01\" my_af <- af %>% filter(allele == my_allele) %>%   filter(n > 1000) %>%   arrange(-alleles_over_2n)  ggplot(my_af) +   aes(x = alleles_over_2n, y = reorder(population, alleles_over_2n)) +   scale_y_discrete(position = \"right\") +   geom_colh() +   labs(     x = \"Allele Frequency (Alleles / 2N)\",     y = NULL,     title =  glue(\"Frequency of {my_allele} across {length(unique(my_af$population))} populations\"),     caption = \"Data from AFND http://allelefrequencies.net\"   )"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"compute-hla-divergence-with-the-grantham-distance-matrix","dir":"Articles","previous_headings":"","what":"Compute HLA divergence with the Grantham distance matrix","title":"hlabud usage examples","text":"Humans diploid, us two copies HLA gene. individual two highly dissimilar alleles can bind greater number different peptides homozygous individual (https://doi.org/10.1007/BF02918202): MHC class II allele capacity bind present specific set peptides processed antigens. inability specific class II allele bind present fragment derived processed antigen results loss immune responsiveness antigen individuals homozygous class II allele. amino acid distance matrix Granthan 1974 (https://doi.org/10.1126/science.185.4154.862) encodes information composition, polarity, molecular volume amino acid. can use matrix compute HLA divergence metric set individuals like : divergence homozygote equal zero, definition: hlabud includes R code divergence calculations translated original Perl code Pierini & Lenz 2018 (https://doi.org/10.1093/molbev/msy116). amino acid distance matrix easily accessible, provide two built-options “grantham” “uniform”:","code":"grantham #>    amino    c    p     v #> 1    Ser 1.42  9.2  32.0 #> 2    Arg 0.65 10.5 124.0 #> 3    Leu 0.00  4.9 111.0 #> 4    Pro 0.39  8.0  32.5 #> 5    Thr 0.71  8.6  61.0 #> 6    Ala 0.00  8.1  31.0 #> 7    Val 0.00  5.9  84.0 #> 8    Gly 0.74  9.0   3.0 #> 9    Ile 0.00  5.2 111.0 #> 10   Phe 0.00  5.2 132.0 #> 11   Tyr 0.20  6.2 136.0 #> 12   Cys 2.75  5.5  55.0 #> 13   His 0.58 10.4  96.0 #> 14   Gln 0.89 10.5  85.0 #> 15   Asn 1.33 11.6  56.0 #> 16   Lys 0.33 11.3 119.0 #> 17   Asp 1.38 13.0  54.0 #> 18   Glu 0.92 12.3  83.0 #> 19   Met 0.00  5.7 105.0 #> 20   Trp 0.13  5.4 170.0 my_genos <- c(\"A*23:01:12,A*24:550\", \"A*25:12N,A*11:27\", \"A*24:381,A*33:85\")  hla_divergence(my_genos) #> A*23:01:12,A*24:550    A*25:12N,A*11:27    A*24:381,A*33:85  #>           0.5131579           3.4736842           5.1078947 hla_divergence(\"A*01:01,A*01:01\") #> A*01:01,A*01:01  #>               0 amino_distance_matrix(method = \"grantham\") #>     A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y #> A   0 112 111 126 195  91 107  60  86  94  96 106  84 113  27  99  58 148 112 #> R 112   0  86  96 180  43  54 125  29  97 102  26  91  97 103 110  71 101  77 #> N 111  86   0  23 139  46  42  80  68 149 153  94 142 158  91  46  65 174 143 #> D 126  96  23   0 154  61  45  94  81 168 172 101 160 177 108  65  85 181 160 #> C 195 180 139 154   0 154 170 159 174 198 198 202 196 205 169 112 149 215 194 #> Q  91  43  46  61 154   0  29  87  24 109 113  53 101 116  76  68  42 130  99 #> E 107  54  42  45 170  29   0  98  40 134 138  56 126 140  93  80  65 152 122 #> G  60 125  80  94 159  87  98   0  98 135 138 127 127 153  42  56  59 184 147 #> H  86  29  68  81 174  24  40  98   0  94  99  32  87 100  77  89  47 115  83 #> I  94  97 149 168 198 109 134 135  94   0   5 102  10  21  95 142  89  61  33 #> L  96 102 153 172 198 113 138 138  99   5   0 107  15  22  98 145  92  61  36 #> K 106  26  94 101 202  53  56 127  32 102 107   0  95 102 103 121  78 110  85 #> M  84  91 142 160 196 101 126 127  87  10  15  95   0  28  87 135  81  67  36 #> F 113  97 158 177 205 116 140 153 100  21  22 102  28   0 114 155 103  40  22 #> P  27 103  91 108 169  76  93  42  77  95  98 103  87 114   0  74  38 147 110 #> S  99 110  46  65 112  68  80  56  89 142 145 121 135 155  74   0  58 177 144 #> T  58  71  65  85 149  42  65  59  47  89  92  78  81 103  38  58   0 128  92 #> W 148 101 174 181 215 130 152 184 115  61  61 110  67  40 147 177 128   0  37 #> Y 112  77 143 160 194  99 122 147  83  33  36  85  36  22 110 144  92  37   0 #> V  64  96 133 152 192  96 121 109  84  29  32  97  21  50  68 124  69  88  55 #>     V #> A  64 #> R  96 #> N 133 #> D 152 #> C 192 #> Q  96 #> E 121 #> G 109 #> H  84 #> I  29 #> L  32 #> K  97 #> M  21 #> F  50 #> P  68 #> S 124 #> T  69 #> W  88 #> Y  55 #> V   0"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"download-and-unpack-all-data-from-the-latest-imgthla-release","dir":"Articles","previous_headings":"","what":"Download and unpack all data from the latest IMGTHLA release","title":"hlabud usage examples","text":"want use hla_alignments(), don’t need install_hla() data files downloaded automatically needed cached future use. users might need access additional files present full data release. Run install_hla() download unpack latest IMGTHLA release. destination folder downloaded data files getOption(\"hlabud_dir\") (automatically tailored operating system thanks rappdirs package). examples download releases get list release names. Download latest release (default) specific release: Optionally, get set directory hlabud uses store data: installing releases, hlabud folder might look like :","code":"# Download all of the data (120MB) for the latest IMGTHLA release install_hla(release = \"latest\")  # Download a specific release install_hla(release = \"3.51.0\") getOption(\"hlabud_dir\") #> [1] \"/home/username/.local/share/hlabud\"  # Manually override the directory for hlabud to use options(hlabud_dir = \"/path/to/my/dir\") ❯ ls -lah \"/home/user/.local/share/hlabud\" total 207M drwxrwxr-x  3 user user      32 Apr  5 01:19 3.30.0 drwxrwxr-x 11 user user    4.0K Apr  7 19:31 3.40.0 drwxrwxr-x 12 user user    4.0K Apr  5 00:27 3.51.0 -rw-rw-r--  1 user user     15K Apr  7 19:23 tags.json -rw-rw-r--  1 user user     79M Apr  7 19:28 v3.40.0-alpha.tar.gz -rw-rw-r--  1 user user    129M Apr  4 20:07 v3.51.0-alpha.tar.gz"},{"path":"https://slowkow.github.io/hlabud/articles/examples.html","id":"count-the-number-of-alleles-in-each-imgthla-release","dir":"Articles","previous_headings":"","what":"Count the number of alleles in each IMGTHLA release","title":"hlabud usage examples","text":"can get list release names: can get allele names release: Next, count many alleles release: plot number alleles line plot:","code":"releases <- hla_releases() releases #>  [1] \"3.56.0\"   \"3.55.0\"   \"3.54.0\"   \"3.53.0\"   \"3.52.0\"   \"3.51.0\"   #>  [7] \"3.50.0\"   \"3.49.0\"   \"3.48.0\"   \"3.47.0\"   \"3.46.0\"   \"3.45.1\"   #> [13] \"3.45.01\"  \"3.45.0.1\" \"3.45.0\"   \"3.44.1\"   \"3.44.0\"   \"3.43.0\"   #> [19] \"3.42.0\"   \"3.41.2\"   \"3.41.0\"   \"3.40.0\"   \"3.39.0\"   \"3.38.0\"   #> [25] \"3.37.0\"   \"3.36.0\"   \"3.35.0\"   \"3.34.0\"   \"3.33.0\"   \"3.32.0\" my_alleles <- rbindlist(lapply(releases, function(release) {   retval <- hla_alleles(release = release)   retval$release <- release   return(retval) }), fill = TRUE) #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.3451.txt' #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.34501.txt' #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.34501.txt' #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.3441.txt' #> Warning in hla_alleles(release = release): unrecognized release name #> 'Allelelist.3412.txt' d <- my_alleles %>% count(release) %>% filter(n > 1) d #>     release     n #>        #>  1:  3.32.0 18363 #>  2:  3.33.0 18955 #>  3:  3.34.0 20272 #>  4:  3.35.0 21683 #>  5:  3.36.0 22548 #>  6:  3.37.0 24093 #>  7:  3.38.0 25958 #>  8:  3.39.0 26512 #>  9:  3.40.0 27273 #> 10:  3.41.0 27980 #> 11:  3.42.0 28786 #> 12:  3.43.0 29417 #> 13:  3.44.0 30523 #> 14:  3.45.0 31552 #> 15:  3.46.0 32330 #> 16:  3.47.0 33552 #> 17:  3.48.0 34145 #> 18:  3.49.0 35077 #> 19:  3.50.0 36016 #> 20:  3.51.0 36625 #> 21:  3.52.0 37068 #> 22:  3.53.0 37619 #> 23:  3.54.0 38416 #> 24:  3.55.0 38909 #> 25:  3.56.0 39886 #>     release     n ggplot(d) +   aes(x = release, y = n, group = 1) +   geom_line() +   geom_text(aes(label = release), hjust = 1) +   labs(x = NULL, y = \"Number of alleles\",   title = \"Each release has more HLA alleles\") +   theme(     axis.text.x = element_blank(),     axis.ticks.x = element_blank(),   ) d2 <- my_alleles %>% mutate(gene = str_split_fixed(Allele, \"\\\\*\", 2)[,1]) %>% count(release, gene) ggplot() +   aes(x = release, y = n) +   geom_line(     data = d2,     aes(group = gene, color = gene)   ) +   scale_color_discrete(guide = \"none\") +   geom_text(     data = d2 %>% filter(release == \"3.52.0\"),     mapping = aes(label = gene),     hjust = 0   ) +   labs(x = NULL, y = \"Number of alleles\",   title = \"Number of alleles per release and gene\") +   scale_x_discrete(expand = expansion(mult = c(0.01, 0.1))) +   scale_y_log10() +   theme(     panel.grid.major.y = element_line(),      axis.text.x = element_blank(),     axis.ticks.x = element_blank(),   )"},{"path":"https://slowkow.github.io/hlabud/articles/numbering.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Numbering amino acid positions","text":"Kamil Slowikowski 2024-06-05 IMGTHLA provides Github repo alignments amino acid sequences nucleotide sequences thousands alleles HLA genes. IMGTHLA alignments define official numbering scheme, provide explanations conventions help page. hlabud R package provides easy access alignment data, hlabud follows official numbering scheme. examples help beginners visualize understand conventions work.","code":""},{"path":"https://slowkow.github.io/hlabud/articles/numbering.html","id":"alignment-files-on-the-imgthla-github-page","dir":"Articles","previous_headings":"","what":"Alignment files on the IMGTHLA Github page","title":"Numbering amino acid positions","text":"IMGTHLA Github page provides folder alignment files.  examples vignette, use HLA-DRB1 gene. DRB1, can find three separate files: https://raw.githubusercontent.com/ANHIG/IMGTHLA/v3.56.0-alpha/alignments/DRB1_gen.txt https://raw.githubusercontent.com/ANHIG/IMGTHLA/v3.56.0-alpha/alignments/DRB1_nuc.txt https://raw.githubusercontent.com/ANHIG/IMGTHLA/v3.56.0-alpha/alignments/DRB1_prot.txt files contain different information: gen contains genomic DNA sequences. nuc contains nucleotide coding sequences (CDS). prot contains protein sequences (amino acids). Let’s consider DRB1_prot.txt file. file look like?  plain text file header sequence alignments. alignment, line represents one sequence (allele), line 100 residues. first 100 residues alleles shown first block. , next block next 100 residues alleles, .","code":""},{"path":"https://slowkow.github.io/hlabud/articles/numbering.html","id":"numbering-conventions","dir":"Articles","previous_headings":"Alignment files on the IMGTHLA Github page","what":"Numbering conventions","title":"Numbering amino acid positions","text":"conventions used alignments (copied EBI): entry allele displayed respect reference sequences. identity reference sequence present base displayed hyphen (-). Non-identity reference sequence shown displaying appropriate base position. insertion deletion occurred represented period (.). sequence unknown point alignment, represented asterisk (*). protein alignments null alleles, ‘Stop’ codons represented hash (X). protein alignments, sequence following termination codon, marked appear blank. conventions used nucleotide protein alignments. ’s lot information! Let’s try work example illustrate works. first sequence alignment reference sequence. position numbering relative reference sequence. means deletions (.) reference sequence numbered. Notice numbering starts negative numbers. help page clarifies: Protein Sequence Numbering amino acid-based systems, start codon mature protein labeled codon 1. codon 5’ numbered -1. numbering based reference sequence. amino acid number 0.","code":""},{"path":"https://slowkow.github.io/hlabud/articles/numbering.html","id":"numbering-indels","dir":"Articles","previous_headings":"Alignment files on the IMGTHLA Github page","what":"Numbering indels","title":"Numbering amino acid positions","text":"alignment shows 100 residues displayed chunks 10:  numbering convention says indels reference sequence numbered. clarify point, manually added additional numbers (11, 21, 30, 39, 49, 59) alignment :  Notice move first chunk GDTRPRFLWQ next chunk LKFECHFFNG simply add 10 1 get 11 number L amino acid. , move TERVR.LLER, add 10 11 get 21 T amino acid. However, move CIYNQEE.SV rule “add 10” work. Instead labeling C position 31, label position 30. ? reason C 30, 31, indel (gap) reference sequence position 25_26 (notice . R.L). convention deletions reference sequence numbered. Let’s take closer look data hlabud. first amino acid positions first 4 sequences: hlabud numbers positions focusing example: hlabud using correct numbering, see: T position 21 C position 30 see positions 25, 26, 25_26? alignment file:  result hlabud: , can see deletion positions 25 26 numbered like residues. Instead, gets special label (25_26) consists positions flanking indel (25 26). alleles observe position 25_26? three possibilities position 25_26: . indicates deletion 1 amino acid (absence amino position) * indicates sequence unknown position W indicates tryptophan position hope example helps explain numbering indels. notice discrepancy hlabud IMGT, please report .","code":"library(hlabud) a <- hla_alignments(\"DRB1\", release = \"3.56.0\") seqs <- substr(a$sequences[1:4], 30, 89) str_replace_all(seqs, \"(\\\\S{10})\", \"\\\\1 \") #> [1] \"GDTRPRFLWQ LKFECHFFNG TERVR.LLER CIYNQEE.SV RFDSDVGEYR AVTELGRPDA \" #> [2] \"---------- ---------- -----.---- -------.-- ---------- ---------- \" #> [3] \"---------- ---------- -----.---- -------.-- ---------- ---------- \" #> [4] \"---------- ---------- -----.---- -------.-- ---------- ---------- \" colnames(a$alleles)[50:70] #>  [1] \"21\"    \"22\"    \"23\"    \"24\"    \"25\"    \"25_26\" \"26\"    \"27\"    \"28\"    #> [10] \"29\"    \"30\"    \"31\"    \"32\"    \"33\"    \"34\"    \"35\"    \"36\"    \"36_37\" #> [19] \"37\"    \"38\"    \"39\" a$alleles[1,\"21\"] #> [1] \"T\" a$alleles[1,\"30\"] #> [1] \"C\" a$alleles[1,\"25\"] #> [1] \"R\" a$alleles[1,\"26\"] #> [1] \"L\" a$alleles[1,\"25_26\"] #> [1] \".\" table(a$alleles[,\"25_26\"]) #>  #>    .    *    W  #> 3658   12    1"},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Visualize HLA protein structures","text":"Kamil Slowikowski 2024-06-05 vignette, explore different methods visualizing molecular structure HLA proteins. First, ’ll look example use NGLVieweR R package show HLA protein structures. Next, ’ll use PyMOL thing.","code":""},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"what-are-the-pdb-identifiers-for-each-hla-gene","dir":"Articles","previous_headings":"","what":"What are the PDB identifiers for each HLA gene?","title":"Visualize HLA protein structures","text":"list PDB identifiers might consider using represent HLA protein: Also try searching PDB website , e.g., \"HLA-DR\" see appropriate structure analysis.","code":"HLA-A  2xpg HLA-B  2bvp HLA-C  4nt6 HLA-DP 3lqz HLA-DQ 4z7w HLA-DR 3pdo"},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"using-nglviewer","dir":"Articles","previous_headings":"","what":"Using NGLVieweR","title":"Visualize HLA protein structures","text":"Let’s try visualize amino acid PDB position 9 HLA-B protein structure. visualize structure 2bvp Protein Data Bank (PDB). example NGLVieweR R package Niels van der Velden: view , see blue peptide red HLA-B protein. tyrosine PDB position 9 highlighted ball+stick representation, also labeled text label. structure rotating can getter better view. can use hlabud answer questions HLA-B amino acid sequence. first question need ask : IMGT position corresponds tyrosine PDB position 9? need open PDB Sequence Annotations tool order figure IMGT number corresponds PDB number 9. screenshot tool: Next, can view amino acid sequence numbering IMGT: eye, can see sequence YFYT starting PDB position 9 corresponds YFYT sequence IMGT position 3. , manually confirmed PDB position 9 matches IMGT position 3. Next, might ask HLA-B alleles Y3? fraction reported HLA-B alleles tyrosine IMGT position 3 (Y3)? turns , almost HLA-B alleles Y3.","code":"# devtools::install_github(\"nvelden/NGLVieweR\") # we need the latest version library(NGLVieweR) library(magrittr) my_sele <- \"9:A\" NGLVieweR(\"2bvp\") %>%   stageParameters(     backgroundColor = \"white\",     zoomSpeed = 1,     cameraFov = 80   ) %>%   addRepresentation(     type = \"cartoon\"   ) %>%   addRepresentation(     type = \"ball+stick\",     param = list(       sele = my_sele     )   ) %>%   addRepresentation(     type = \"label\",     param = list(       sele = my_sele,       labelType = \"format\",       labelFormat = \"[%(resname)s]%(resno)s\", # or enter custom text       labelGrouping = \"residue\", # or \"atom\" (eg. sele = \"20:A.CB\")       color = \"black\",       fontFamiliy = \"sans-serif\",       xOffset = 1,       yOffset = 0,       zOffset = 0,       fixedSize = TRUE,       radiusType = 1,       radiusSize = 5.5, # Label size       showBackground = TRUE       # backgroundColor=\"black\",       # backgroundOpacity=0.5     )   ) %>%   zoomMove(     center = my_sele,     zoom = my_sele,     duration = 0, # animation time in ms     z_offSet = -20   ) %>%   setSpin() library(hlabud) a <- hla_alignments(\"B\") library(stringr) a$alleles[which(str_detect(rownames(a$alleles), \"B*57:03\")),][1,1:50] #>      n30      n29      n28      n27      n26      n25      n24      n23  #>      \"M\"      \"R\"      \"V\"      \"T\"      \"A\"      \"P\"      \"R\"      \"T\"  #>      n22  n22_n21      n21      n20      n19      n18      n17      n16  #>      \"V\" \"......\"      \"L\"      \"L\"      \"L\"      \"L\"      \"W\"      \"G\"  #>      n15      n14      n13      n12      n11      n10       n9       n8  #>      \"A\"      \"V\"      \"A\"      \"L\"      \"T\"      \"E\"      \"T\"      \"W\"  #>       n7       n6       n5       n4       n3       n2       n1        1  #>      \"A\"      \"G\"      \"S\"      \"H\"      \"S\"      \"M\"      \"R\"      \"Y\"  #>        2        3        4        5        6        7        8        9  #>      \"F\"      \"Y\"      \"T\"      \"A\"      \"M\"      \"S\"      \"R\"      \"P\"  #>       10       11       12       13       14       15       16       17  #>      \"G\"      \"R\"      \"G\"      \"E\"      \"P\"      \"R\"      \"F\"      \"I\"  #>       18    18_19  #>      \"A\"  \".....\" my_alleles <- names(which(a$onehot[,\"Y3\"] == 1)) length(my_alleles) #> [1] 7023 head(my_alleles, 20) #>  [1] \"B*07:02:01:01\" \"B*07:02:01:02\" \"B*07:02:01:03\" \"B*07:02:01:04\" #>  [5] \"B*07:02:01:05\" \"B*07:02:01:06\" \"B*07:02:01:07\" \"B*07:02:01:08\" #>  [9] \"B*07:02:01:09\" \"B*07:02:01:10\" \"B*07:02:01:11\" \"B*07:02:01:12\" #> [13] \"B*07:02:01:13\" \"B*07:02:01:14\" \"B*07:02:01:15\" \"B*07:02:01:16\" #> [17] \"B*07:02:01:17\" \"B*07:02:01:18\" \"B*07:02:01:19\" \"B*07:02:01:20\" sum(a$onehot[,\"Y3\"] == 1) / nrow(a$onehot) #> [1] 0.711406"},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"using-pymol","dir":"Articles","previous_headings":"","what":"Using PyMOL","title":"Visualize HLA protein structures","text":"PyMOL one favorite methods visualizing protein structures, allows us change residue existing protein visualize new mutated protein. takes lines PyMOL create nice figure. example, want quickly highlight positions 13 45 HLA-DQB1, snippet PyMOL code produce figure . Bash script : Write PyMOL script Run PyMOL script pymol command PyMOL script : Load structure Protein Data Bank (PDB). 7kei identifier published protein structure. Color HLA-DQA1 protein teal. Color HLA-DQB1 protein orange. Color peptide purple. color residues 13 45 HLA-DQB1 red. Label residues positions names. Write PNG file view structure.  image , manually rotated structure mouse added text labels like \"PDB: 7kei\" saving file.","code":"#!/usr/bin/env bash  # Write a pymol script cat << EOF > script.pml fetch 7kei show cartoon remove solvent remove chain D remove chain H color teal, chain A color orange, chain B color purple, chain C color red, chain B & resi 13 color red, chain B & resi 45 label n. CA and chain B & resi 13, \"%s %s\" % (resi, resn) label n. CA and chain B & resi 45, \"%s %s\" % (resi, resn) png 7kei.png, width=1200, height=800, dpi=300  EOF  # On Linux, we can just use `pymol` without making an alias  # On macOS, we need to make an alias alias pymol=/Applications/PyMOL.app/Contents/MacOS/PyMOL  pymol -c script.pml"},{"path":"https://slowkow.github.io/hlabud/articles/visualize-hla-structure.html","id":"other-software-for-viewing-pdb-data","dir":"Articles","previous_headings":"","what":"Other software for viewing PDB data","title":"Visualize HLA protein structures","text":"ChimeraX: https://www.cgl.ucsf.edu/chimerax/ Python: https://github.com/nglviewer/nglview Javascript: https://www.rcsb.org/3d-view https://www.ncbi.nlm.nih.gov/Structure/icn3d/full.html?mmdbid=7kei&bu=1 https://github.com/nglviewer/ngl https://github.com/biasmv/pv R: https://www.raymolecule.com","code":""},{"path":"https://slowkow.github.io/hlabud/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Kamil Slowikowski. Author, maintainer.","code":""},{"path":"https://slowkow.github.io/hlabud/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"J R, DJ B, X G, MA C, P F, SGE. M (2019). “IPD-IMGT/HLA Database.” Nucleic Acids Research, 48(D1), D948–D955. doi:10.1093/nar/gkz950. Slowikowski K (2023). hlabud: IMGTHLA Data R. doi:10.5281/zenodo.8183949, R package version 2.0.0, https://github.com/slowkow/hlabud.","code":"@Article{,   author = {Robinson J and Barker DJ and Georgiou X and Cooper MA and Flicek P and Marsh SGE.},   title = {IPD-IMGT/HLA Database},   doi = {10.1093/nar/gkz950},   year = {2019},   month = {oct},   publisher = {Oxford University Press},   volume = {48},   number = {D1},   pages = {D948–D955},   journal = {Nucleic Acids Research}, } @Manual{,   title = {{hlabud}: IMGTHLA Data from R},   author = {Kamil Slowikowski},   year = {2023},   note = {R package version 2.0.0},   doi = {10.5281/zenodo.8183949},   url = {https://github.com/slowkow/hlabud}, }"},{"path":"https://slowkow.github.io/hlabud/index.html","id":"hlabud-hla-analysis-in-r-","dir":"","previous_headings":"","what":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"hlabud provides methods retrieve sequence alignment data IMGTHLA convert data convenient R matrices ready downstream analysis. See usage examples learn use data logistic regression dimensionality reduction. example, let’s consider simple question two HLA genotypes. amino acid positions different two genotypes? output, can conclude four positions (26, 28, 47, 86) distinguish two HLA-DRB1 alleles. see DRB1*03:01:05 Y position 26 DRB1*03:02:03 F.","code":"library(hlabud) a <- hla_alignments(\"DRB1\") dosage(a$onehot, c(\"DRB1*03:01:05\", \"DRB1*03:02:03\"))  ##               F26 Y26 D28 E28 F47 Y47 G86 V86 ## DRB1*03:01:05   0   1   1   0   1   0   0   1 ## DRB1*03:02:03   1   0   0   1   0   1   1   0"},{"path":"https://slowkow.github.io/hlabud/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"quickest way get hlabud install GitHub:","code":"# install.packages(\"devtools\") devtools::install_github(\"slowkow/hlabud\")"},{"path":"https://slowkow.github.io/hlabud/index.html","id":"examples","dir":"","previous_headings":"","what":"Examples","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"See usage examples get ideas use hlabud analyses. Get one-hot encoded matrix HLA-DRB1 alleles Convert genotypes dosage matrix Logistic regression association amino acid positions UMAP embedding 3,671 HLA-DRB1 alleles Get HLA allele frequencies Allele Frequency Net Database (AFND) Compute HLA divergence Grantham distance matrix Download unpack data latest IMGTHLA release Visualize 3D molecular structure HLA proteins highlight specific amino acid residues","code":""},{"path":"https://slowkow.github.io/hlabud/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"hlabud provides access data IMGT/HLA database. Therefore, use hlabud please cite IMGT/HLA paper: Robinson J, Barker DJ, Georgiou X, Cooper MA, Flicek P, Marsh SGE. IPD-IMGT/HLA Database. Nucleic Acids Res. 2020;48: D948–D955. doi:10.1093/nar/gkz950 hlabud also provides access data Allele Frequency Net Database (AFND). Therefore, use hlabud::hla_frequencies() please cite AFND paper: Gonzalez-Galarza FF, McCabe , Santos EJMD, Jones J, Takeshita L, Ortega-Rivera ND, et al. Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data new query tools. Nucleic Acids Res. 2020;48: D783–D788. doi:10.1093/nar/gkz1029 Additionally, can also cite hlabud package like : Slowikowski K. hlabud: methods access analysis human leukocyte antigen (HLA) gene sequence alignments IMGT/HLA. R package version 1.0.0.","code":""},{"path":"https://slowkow.github.io/hlabud/index.html","id":"related-work","dir":"","previous_headings":"","what":"Related work","title":"Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA","text":"recommend article anyone new HLA, beautiful figures help build intuition: La Gruta NL, Gras S, Daley SR, Thomas PG, Rossjohn J. Understanding drivers MHC restriction T cell receptors. Nat Rev Immunol. 2018;18: 467–478. Learn conventions HLA nomenclature: Marsh SGE, Albert ED, Bodmer WF, Bontrop RE, Dupont B, Erlich HA, et al. Nomenclature factors HLA system, 2010. Tissue Antigens. 2010;75: 291–455. case-control analysis HLA genotype data, consider BIGDAWG R package available CRAN. related article: Pappas DJ, Marin W, Hollenbach JA, Mack SJ. Bridging ImmunoGenomic Data Analysis Workflow Gaps (BIGDAWG): integrated case-control analysis pipeline. Hum Immunol. 2016;77: 283–287.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"default, return amino acid distance matrix Grantham 1974 (doi:10.1126/science.185.4154.862).","code":""},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"","code":"amino_distance_matrix(method = \"grantham\")"},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"method \"grantham\" Grantham 1974 matrix \"uniform\" matrix ones non-diagonal.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"20x20 symmetric matrix positive numbers zeros diagonal.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/amino_distance_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a pairwise 20x20 distance matrix for all pairs of amino acids — amino_distance_matrix","text":"","code":"# By default, the Grantham 1974 matrix amino_distance_matrix(\"grantham\") #>     A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y #> A   0 112 111 126 195  91 107  60  86  94  96 106  84 113  27  99  58 148 112 #> R 112   0  86  96 180  43  54 125  29  97 102  26  91  97 103 110  71 101  77 #> N 111  86   0  23 139  46  42  80  68 149 153  94 142 158  91  46  65 174 143 #> D 126  96  23   0 154  61  45  94  81 168 172 101 160 177 108  65  85 181 160 #> C 195 180 139 154   0 154 170 159 174 198 198 202 196 205 169 112 149 215 194 #> Q  91  43  46  61 154   0  29  87  24 109 113  53 101 116  76  68  42 130  99 #> E 107  54  42  45 170  29   0  98  40 134 138  56 126 140  93  80  65 152 122 #> G  60 125  80  94 159  87  98   0  98 135 138 127 127 153  42  56  59 184 147 #> H  86  29  68  81 174  24  40  98   0  94  99  32  87 100  77  89  47 115  83 #> I  94  97 149 168 198 109 134 135  94   0   5 102  10  21  95 142  89  61  33 #> L  96 102 153 172 198 113 138 138  99   5   0 107  15  22  98 145  92  61  36 #> K 106  26  94 101 202  53  56 127  32 102 107   0  95 102 103 121  78 110  85 #> M  84  91 142 160 196 101 126 127  87  10  15  95   0  28  87 135  81  67  36 #> F 113  97 158 177 205 116 140 153 100  21  22 102  28   0 114 155 103  40  22 #> P  27 103  91 108 169  76  93  42  77  95  98 103  87 114   0  74  38 147 110 #> S  99 110  46  65 112  68  80  56  89 142 145 121 135 155  74   0  58 177 144 #> T  58  71  65  85 149  42  65  59  47  89  92  78  81 103  38  58   0 128  92 #> W 148 101 174 181 215 130 152 184 115  61  61 110  67  40 147 177 128   0  37 #> Y 112  77 143 160 194  99 122 147  83  33  36  85  36  22 110 144  92  37   0 #> V  64  96 133 152 192  96 121 109  84  29  32  97  21  50  68 124  69  88  55 #>     V #> A  64 #> R  96 #> N 133 #> D 152 #> C 192 #> Q  96 #> E 121 #> G 109 #> H  84 #> I  29 #> L  32 #> K  97 #> M  21 #> F  50 #> P  68 #> S 124 #> T  69 #> W  88 #> Y  55 #> V   0  # All ones, and zeros on the diagonal amino_distance_matrix(\"uniform\") #>   A R N D C Q E G H I L K M F P S T W Y V #> A 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> R 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> N 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> D 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> C 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> Q 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> E 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 #> G 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 #> H 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 #> I 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 #> L 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 #> K 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 #> M 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 #> F 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 #> P 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 #> S 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 #> T 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 #> W 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 #> Y 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 #> V 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0"},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"genotype name, return dosage matrix residue (amino acid nucleotide) position.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"","code":"dosage(   mat,   names,   drop_constants = TRUE,   drop_duplicates = FALSE,   verbose = FALSE )"},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"mat one-hot encoded matrix one row per allele one column residue (amino acid nucleotide) position. names Input character vector one genotype individual. entries must present rownames(mat). drop_constants Filter constant amino acid positions. TRUE default. drop_duplicates Filter duplicate amino acid positions. FALSE default. verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"matrix one row input genotype, one column residue position.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"genotype represented like \"HLA-*01:01,HLA-*01:01\" default, returned matrix filtered exclude: positions input genotypes allele","code":""},{"path":"https://slowkow.github.io/hlabud/reference/dosage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a set of genotype names into a dosage matrix of each residue at each position — dosage","text":"","code":"DRB1_file <- file.path(   \"https://github.com/ANHIG/IMGTHLA/raw\",   \"5f2c562056f8ffa89aeea0631f2a52300ee0de17\",   \"alignments/DRB1_prot.txt\" ) a <- read_alignments(DRB1_file) genotypes <- c(   \"DRB1*12:02:02:03,DRB1*12:02:02:03,DRB1*14:54:02\",   \"DRB1*04:174,DRB1*15:152\",   \"DRB1*04:56:02,DRB1*15:01:48\",   \"DRB1*14:172,DRB1*04:160\",   \"DRB1*04:359,DRB1*04:284:02\" ) dosage <- dosage(a$onehot, genotypes) dosage[,1:5] #>                                                 n29unk Mn29 n28unk Vn28 n27unk #> DRB1*12:02:02:03,DRB1*12:02:02:03,DRB1*14:54:02      1    2      1    2      1 #> DRB1*04:174,DRB1*15:152                              2    0      2    0      2 #> DRB1*04:56:02,DRB1*15:01:48                          2    0      2    0      2 #> DRB1*14:172,DRB1*04:160                              2    0      2    0      2 #> DRB1*04:359,DRB1*04:284:02                           2    0      2    0      2"},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"function : Get folder name getOption(\"hlabud_dir\") else automatically choose appropriate folder operating system thanks rappdirs. Create folder automatically already exist. Set hlabud_dir option new folder.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"","code":"get_hlabud_dir()"},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"name folder.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"locations hlabud_dir folder operating system. Linux:   Mac:   Windows:   set hlabud_dir option, please use:","code":"~/.local/share/hlabud ~/Library/Application Support/hlabud C:\\Documents and Settings\\{User}\\Application Data\\slowkow\\hlabud options(hlabud_dir = \"/my/favorite/path\")"},{"path":"https://slowkow.github.io/hlabud/reference/get_hlabud_dir.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the name of the folder for caching downloaded IMGTHLA files — get_hlabud_dir","text":"","code":"if (FALSE) { hlabud_dir <- get_hlabud_dir() }"},{"path":"https://slowkow.github.io/hlabud/reference/get_onehot.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a one-hot encoded matrix from a dataframe of amino acid sequences. — get_onehot","title":"Make a one-hot encoded matrix from a dataframe of amino acid sequences. — get_onehot","text":"Make one-hot encoded matrix dataframe amino acid sequences.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/get_onehot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a one-hot encoded matrix from a dataframe of amino acid sequences. — get_onehot","text":"","code":"get_onehot(sequences, n_pre, verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/get_onehot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a one-hot encoded matrix from a dataframe of amino acid sequences. — get_onehot","text":"n_pre number amino acid sequences position 1. verbose Print messages along way. al dataframe columns allele, seq","code":""},{"path":"https://slowkow.github.io/hlabud/reference/grantham.html","id":null,"dir":"Reference","previous_headings":"","what":"Table 1 from Grantham 1974 — grantham","title":"Table 1 from Grantham 1974 — grantham","text":"Grantham R. Amino Acid Difference Formula Help Explain Protein Evolution. Science. 1974;185: 862–864. doi:10.1126/science.185.4154.862","code":""},{"path":"https://slowkow.github.io/hlabud/reference/grantham.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Table 1 from Grantham 1974 — grantham","text":"","code":"grantham"},{"path":"https://slowkow.github.io/hlabud/reference/grantham.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Table 1 from Grantham 1974 — grantham","text":"data frame 20 rows 5 columns: amino Amino acid c Composition c, atomic weight ratio noncarbon elements end groups rings carbons side chain p Polarity p published data v Volume v published data","code":""},{"path":"https://slowkow.github.io/hlabud/reference/grantham.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Table 1 from Grantham 1974 — grantham","text":"","code":"grantham #>    amino    c    p     v #> 1    Ser 1.42  9.2  32.0 #> 2    Arg 0.65 10.5 124.0 #> 3    Leu 0.00  4.9 111.0 #> 4    Pro 0.39  8.0  32.5 #> 5    Thr 0.71  8.6  61.0 #> 6    Ala 0.00  8.1  31.0 #> 7    Val 0.00  5.9  84.0 #> 8    Gly 0.74  9.0   3.0 #> 9    Ile 0.00  5.2 111.0 #> 10   Phe 0.00  5.2 132.0 #> 11   Tyr 0.20  6.2 136.0 #> 12   Cys 2.75  5.5  55.0 #> 13   His 0.58 10.4  96.0 #> 14   Gln 0.89 10.5  85.0 #> 15   Asn 1.33 11.6  56.0 #> 16   Lys 0.33 11.3 119.0 #> 17   Asp 1.38 13.0  54.0 #> 18   Glu 0.92 12.3  83.0 #> 19   Met 0.00  5.7 105.0 #> 20   Trp 0.13  5.4 170.0"},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":null,"dir":"Reference","previous_headings":"","what":"Get sequence alignments from IMGTHLA — hla_alignments","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"conventions used alignments (EBI IMGT-HLA help page): entry allele displayed respect reference sequences. identity reference sequence present base displayed hyphen (-). Non-identity reference sequence shown displaying appropriate base position. insertion deletion occurred represented period (.). sequence unknown point alignment, represented asterisk (*). protein alignments null alleles, 'Stop' codons represented hash (X). protein alignments, sequence following termination codon, marked appear blank. conventions used nucleotide protein alignments.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"","code":"hla_alignments(   gene = \"DRB1\",   type = \"prot\",   release = \"latest\",   verbose = FALSE )"},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"gene name gene like \"DRB1\" type type sequence, one \"prot\", \"nuc\", \"gen\" release Default \"latest\". release name like \"3.51.0\". verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"list character vector called sequences two matrices called alleles onehot. character vector sequences one sequence allele, names allele names. matrix alleles one row allele, one column position, values representing residues position allele. matrix onehot one-hot encoding variants distinguish alleles, one row allele one column amino acid position.","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hla_alignments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get sequence alignments from IMGTHLA — hla_alignments","text":"","code":"# \\donttest{ a <- hla_alignments(\"DRB1\") head(a$sequences) #>                                                                                                                                                                                                                                                                DRB1*01:01:01:01  #> \"MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGTERVR.LLERCIYNQEE.SVRFDSDVGEYRAVTELGRPDAEYWNSQKDLLEQRRAAVDTYCRHNYGVGESFTVQRR.VEPKVTVYPSKTQPLQHHNLLVCSVSGFYPGSIEVRWFRNGQEEKAGVVSTGLIQNGDWTFQTLVMLETVPRSGEVYTCQVEHPSVTSPLTVEWRARSESAQSKMLSGVGGFVLGLLFLGAGLFIYFRNQKGHSGLQPTGFLS\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:02  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:03  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:04  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:05  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:06  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  a$alleles[1:6,1:6] #>                  n29 n28 n27 n26 n25 n24 #> DRB1*01:01:01:01 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:02 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:03 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:04 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:05 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" #> DRB1*01:01:01:06 \"M\" \"V\" \"C\" \"L\" \"K\" \"L\" a$onehot[1:6,1:6] #>                  n29unk Mn29 n28unk Ln28 Vn28 n27unk #> DRB1*01:01:01:01      0    1      0    0    1      0 #> DRB1*01:01:01:02      0    1      0    0    1      0 #> DRB1*01:01:01:03      0    1      0    0    1      0 #> DRB1*01:01:01:04      0    1      0    0    1      0 #> DRB1*01:01:01:05      0    1      0    0    1      0 #> DRB1*01:01:01:06      0    1      0    0    1      0 # }"},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"Download list allele names HLA genes particular IMGTHLA release.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"","code":"hla_alleles(release = \"latest\", overwrite = FALSE, verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"release Default \"latest\". release name like \"3.51.0\". overwrite Overwrite existing alleles.json file Allelelist.{version}.txt file verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"data frame HLA allele ids names","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hla_alleles.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a table of allele names for a particular IMGTHLA release — hla_alleles","text":"","code":"# \\donttest{ head(hla_alleles()) #>   AlleleID         Allele #> 1 HLA00001  A*01:01:01:01 #> 2 HLA02169 A*01:01:01:02N #> 3 HLA14798  A*01:01:01:03 #> 4 HLA15760  A*01:01:01:04 #> 5 HLA16415  A*01:01:01:05 #> 6 HLA16417  A*01:01:01:06 # }"},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate HLA divergence for each individual — hla_divergence","title":"Calculate HLA divergence for each individual — hla_divergence","text":"First, convert allele name (e.g. *01:01) amino acid sequence. divergence sum distances pair amino acids position, divided total sequence length. amino acid distance matrix use one published Grantham 1974 (doi:10.1126/science.185.4154.862), based three physical properties amino acids (composition, polarity, molecular volume) correlated estimate relative substitution frequency.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate HLA divergence for each individual — hla_divergence","text":"","code":"hla_divergence(   alleles = c(\"A*01:01,A*02:01\"),   method = \"grantham\",   release = \"latest\",   verbose = FALSE )"},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate HLA divergence for each individual — hla_divergence","text":"alleles character vector comma-delimited alleles individual. usually expect two alleles per individual, possible (fewer) copies due copy number alterations. function still works individual different number alleles. method pairwise amino acid matrix, method name: \"grantham\" \"uniform\" indicate pairwise amino acid distance matrix use. choose pass matrix, 20x20 symmetric matrix zeros diagonal, rownames colnames one-letter amino acid codes R N D C Q E G H L K M F P S T W Y V. release Default \"latest\". release name like \"3.51.0\". verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate HLA divergence for each individual — hla_divergence","text":"dataframe divergence individual.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate HLA divergence for each individual — hla_divergence","text":"code function translation original Perl code Tobias Lenz, published Pierini & Lenz 2018 MolBiolEvol (https://doi.org/10.1093/molbev/msy116). comparing two amino acid sequences, characters one 20 amino acids considered divergence calculation, gaps (characters) count.","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hla_divergence.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate HLA divergence for each individual — hla_divergence","text":"","code":"my_genos <- c(\"A*23:01:12,A*24:550\", \"A*25:12N,A*11:27\",               \"A*24:381,A*33:85\", \"A*01:01:,A*01:01,A*02:01\") hla_divergence(my_genos, method = \"grantham\") #>      A*23:01:12,A*24:550         A*25:12N,A*11:27         A*24:381,A*33:85  #>                0.5131579                3.4736842                5.1078947  #> A*01:01:,A*01:01,A*02:01  #>                3.9982456   # This is equivalent hla_divergence(my_genos, method = amino_distance_matrix(\"grantham\")) #>      A*23:01:12,A*24:550         A*25:12N,A*11:27         A*24:381,A*33:85  #>                0.5131579                3.4736842                5.1078947  #> A*01:01:,A*01:01,A*02:01  #>                3.9982456"},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":null,"dir":"Reference","previous_headings":"","what":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"Download read table HLA allele frequencies Allele Frequency Net Database (AFND).","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"","code":"hla_frequencies(verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"dataframe HLA allele frequencies genes.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"use data, please cite latest manuscript Allele Frequency Net Database: Gonzalez-Galarza FF, McCabe , Santos EJMD, Jones J, Takeshita L, Ortega-Rivera ND, et al. Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data new query tools. Nucleic Acids Res. 2020;48: D783–D788. doi:10.1093/nar/gkz1029","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_frequencies.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get HLA frequences from Allele Frequency Net Database (AFND) — hla_frequencies","text":"","code":"# \\donttest{ hla_frequencies() #> # A tibble: 123,502 × 7 #>    group gene  allele  population            indivs_over_n alleles_over_2n     n #>                                               #>  1 hla   A     A*01:01 Argentina Rosario To…          15.1           0.076    86 #>  2 hla   A     A*01:01 Armenia combined Reg…          NA             0.125   100 #>  3 hla   A     A*01:01 Australia Cape York …          NA             0.053   103 #>  4 hla   A     A*01:01 Australia Groote Eyl…          NA             0.027    75 #>  5 hla   A     A*01:01 Australia New South …          NA             0.187   134 #>  6 hla   A     A*01:01 Australia Yuendumu A…          NA             0.008   191 #>  7 hla   A     A*01:01 Austria                        27             0.146   200 #>  8 hla   A     A*01:01 Azores Central Islan…          NA             0.08     59 #>  9 hla   A     A*01:01 Azores Oriental Isla…          NA             0.115    43 #> 10 hla   A     A*01:01 Azores Terceira Isla…          NA             0.109   130 #> # ℹ 123,492 more rows # }"},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Get HLA gene names from IMGTHLA — hla_genes","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"Retrieve list txt files github.com/ANHIG/IMGTHLA/alignments return list gene names derived file names.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"","code":"hla_genes(release = \"latest\", overwrite = FALSE, verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"release Default \"latest\". release name like \"3.51.0\". overwrite Overwrite existing genes.json file new one GitHub verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"tibble two columns: HLA gene names (\"\", \"DRB1\") types (\"nuc\", \"gen\", \"prot\").","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hla_genes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get HLA gene names from IMGTHLA — hla_genes","text":"","code":"# \\donttest{ hla_genes()  #> # A tibble: 107 × 2 #>    gene  type  #>      #>  1 A     gen   #>  2 A     nuc   #>  3 A     prot  #>  4 B     gen   #>  5 B     nuc   #>  6 B     prot  #>  7 C     gen   #>  8 C     nuc   #>  9 C     prot  #> 10 DMA   gen   #> # ℹ 97 more rows # }"},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the names of releases from IMGTHLA — hla_releases","title":"Get the names of releases from IMGTHLA — hla_releases","text":"Get tags github.com/ANHIG/IMGTHLA, save file called tags.json getOption(\"hlabud_dir\"),  return release names file.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the names of releases from IMGTHLA — hla_releases","text":"","code":"hla_releases(overwrite = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the names of releases from IMGTHLA — hla_releases","text":"overwrite Overwrite existing tags.json file getOption(\"hlabud_dir\")","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the names of releases from IMGTHLA — hla_releases","text":"character vector release names like \"3.51.0\"","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the names of releases from IMGTHLA — hla_releases","text":"tags.json file automatically overwritten older 24 hours.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/hla_releases.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the names of releases from IMGTHLA — hla_releases","text":"","code":"# \\donttest{ hla_releases()  #>  [1] \"3.56.0\"   \"3.55.0\"   \"3.54.0\"   \"3.53.0\"   \"3.52.0\"   \"3.51.0\"   #>  [7] \"3.50.0\"   \"3.49.0\"   \"3.48.0\"   \"3.47.0\"   \"3.46.0\"   \"3.45.1\"   #> [13] \"3.45.01\"  \"3.45.0.1\" \"3.45.0\"   \"3.44.1\"   \"3.44.0\"   \"3.43.0\"   #> [19] \"3.42.0\"   \"3.41.2\"   \"3.41.0\"   \"3.40.0\"   \"3.39.0\"   \"3.38.0\"   #> [25] \"3.37.0\"   \"3.36.0\"   \"3.35.0\"   \"3.34.0\"   \"3.33.0\"   \"3.32.0\"   # }"},{"path":"https://slowkow.github.io/hlabud/reference/hlabud-package.html","id":null,"dir":"Reference","previous_headings":"","what":"hlabud: Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA — hlabud-package","title":"hlabud: Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA — hlabud-package","text":"Fetch sequence alignment data IMGTHLA database Robinson et al (2020) doi:10.1093/nar/gkz950 , automatically convert sequence alignments convenient R matrices ready downstream analysis. vignette shows examples using one-hot encoding data logistic regression dimensionality reduction. Data downloaded lazily, -needed, cached user-configurable folder.","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/hlabud-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"hlabud: Methods for Access and Analysis of the Human Leukocyte Antigen (HLA) Gene Sequence Alignments from IMGTHLA — hlabud-package","text":"Maintainer: Kamil Slowikowski kslowikowski@gmail.com (ORCID)","code":""},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and unpack a tarball release from IMGTHLA — install_hla","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"release tarball Github unpacked getOption(\"hlabud_dir\") folder.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"","code":"install_hla(release = \"latest\", overwrite = FALSE, verbose = FALSE)"},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"release Default \"latest\". release name like \"3.51.0\". overwrite TRUE, overwrite existing files release folder. verbose TRUE, print messages along way.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"Note latest releases 100 MB size, download might take slow connections.","code":""},{"path":[]},{"path":"https://slowkow.github.io/hlabud/reference/install_hla.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and unpack a tarball release from IMGTHLA — install_hla","text":"","code":"if (FALSE) { install_hla() install_hla(\"3.51.0\") install_hla(\"3.51.0\", verbose = TRUE) # Change the install directory options(hlabud_dir = \"path/to/my/dir\") install_hla() }"},{"path":"https://slowkow.github.io/hlabud/reference/one_to_three.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert one letter amino acid codes to three letter amino acid codes — one_to_three","title":"Convert one letter amino acid codes to three letter amino acid codes — one_to_three","text":"Convert one letter amino acid codes three letter amino acid codes","code":""},{"path":"https://slowkow.github.io/hlabud/reference/one_to_three.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert one letter amino acid codes to three letter amino acid codes — one_to_three","text":"","code":"one_to_three(aminos)"},{"path":"https://slowkow.github.io/hlabud/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":null,"dir":"Reference","previous_headings":"","what":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"function reads txt files provided IMGTHLA.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"","code":"read_alignments(file)"},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"file File name txt file IMGTHLA like \"DQB1_prot.txt\"","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"list character vector called sequences two matrices alleles onehot. matrix alleles one row allele, one column position, values representing residues position allele. matrix onehot one-hot encoding variants distinguish alleles, one row allele one column amino acid position.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"Consider using hla_alignments() instead function. already txt file want read, can read read_alignments(\"myfile.txt\"). sequences contained file: {gene}_prot.txt amino acid sequence HLA allele. {gene}_nuc.txt nucleotide sequence exons. {gene}_gen.txt genomic sequence exons introns.","code":""},{"path":"https://slowkow.github.io/hlabud/reference/read_alignments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read an alignment file *_(nuc|gen|prot).txt from IMGTHLA — read_alignments","text":"","code":"my_file <- file.path(   \"https://github.com/ANHIG/IMGTHLA/raw\",   \"5f2c562056f8ffa89aeea0631f2a52300ee0de17\",   \"alignments/DRB1_prot.txt\" ) a <- read_alignments(my_file) head(a$sequences) #>                                                                                                                                                                                                                                                                DRB1*01:01:01:01  #> \"MVCLKLPGGSCMTALTVTLMVLSSPLALAGDTRPRFLWQLKFECHFFNGTERVR.LLERCIYNQEE.SVRFDSDVGEYRAVTELGRPDAEYWNSQKDLLEQRRAAVDTYCRHNYGVGESFTVQRR.VEPKVTVYPSKTQPLQHHNLLVCSVSGFYPGSIEVRWFRNGQEEKAGVVSTGLIQNGDWTFQTLVMLETVPRSGEVYTCQVEHPSVTSPLTVEWRARSESAQSKMLSGVGGFVLGLLFLGAGLFIYFRNQKGHSGLQPTGFLS\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:02  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:03  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:04  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:05  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  #>                                                                                                                                                                                                                                                                DRB1*01:01:01:06  #> \"------------------------------------------------------.-----------.----------------------------------------------------------.-----------------------------------------------------------------------------------------------------------------------------------------------\"  a$alleles[1:5,1:5] #>                  n29 n28 n27 n26 n25 #> DRB1*01:01:01:01 \"M\" \"V\" \"C\" \"L\" \"K\" #> DRB1*01:01:01:02 \"M\" \"V\" \"C\" \"L\" \"K\" #> DRB1*01:01:01:03 \"M\" \"V\" \"C\" \"L\" \"K\" #> DRB1*01:01:01:04 \"M\" \"V\" \"C\" \"L\" \"K\" #> DRB1*01:01:01:05 \"M\" \"V\" \"C\" \"L\" \"K\" a$onehot[1:5,1:5] #>                  n29unk Mn29 n28unk Vn28 n27unk #> DRB1*01:01:01:01      0    1      0    1      0 #> DRB1*01:01:01:02      0    1      0    1      0 #> DRB1*01:01:01:03      0    1      0    1      0 #> DRB1*01:01:01:04      0    1      0    1      0 #> DRB1*01:01:01:05      0    1      0    1      0"},{"path":[]},{"path":"https://slowkow.github.io/hlabud/news/index.html","id":"bug-fixes-2-0-0","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"hlabud 2.0.0","text":"Fix incorrect position numbering, accounting insertions deletions indicated “.” character. Thanks Vinicius Stelet bringing attention issue #3. Instead discarding positions *, include label unk, example pos241_unk indicates unknown amino acid position 241. Thanks Sreekar Mantena reporting issue! Fix --one error. example, HLA-pos361_- colnames($onehot) reference allele instead -. now fixed. Thanks Sreekar Mantena reporting issue!","code":""},{"path":"https://slowkow.github.io/hlabud/news/index.html","id":"changes-2-0-0","dir":"Changelog","previous_headings":"","what":"Changes","title":"hlabud 2.0.0","text":"Change position names pos21_D D21. negative, posn21_D Dn21. Change dosage() take one-hot matrix first argument. Change dosage() return full allele names IMGT matching partial allele names like DRB1*03 DRB1*03:01. show messages indicating alleles matched verbose=TRUE. Automatically overwrite {hlabud_dir}/alleles.json older 24 hours. Automatically overwrite {hlabud_dir}/tags.json older 24 hours.","code":""},{"path":"https://slowkow.github.io/hlabud/news/index.html","id":"hlabud-100","dir":"Changelog","previous_headings":"","what":"hlabud 1.0.0","title":"hlabud 1.0.0","text":"Initial release. Added NEWS.md file track changes package.","code":""}]