Removed pbmc_facs.

DESCRIPTION

@@ -1,8 +1,8 @@
 Encoding: UTF-8
 Type: Package
 Package: fastTopics
-Version: 0.6-185
-Date: 2024-06-27
+Version: 0.6-186
+Date: 2024-06-28
 Title: Fast Algorithms for Fitting Topic Models and Non-Negative
  Matrix Factorizations to Count Data
 Authors@R: c(person("Peter","Carbonetto",role=c("aut","cre"),

R/fit_poisson_nmf.R

@@ -449,7 +449,7 @@ fit_poisson_nmf <- function (X, k, fit0, numiter = 100,
  cat(sprintf("Running at most %d %s updates, %s extrapolation ",
  numiter,method.text,
  ifelse(control$extrapolate,"with","without")))
- cat("(fastTopics 0.6-185).\n")
+ cat("(fastTopics 0.6-186).\n")
  }
 
  # INITIALIZE ESTIMATES

R/pbmc_facs.R

@@ -39,14 +39,8 @@
 #'
 #' \item{fit}{Poisson non-negative matrix factorization (NMF) fitted
 #' to the UMI count data \code{counts}, with rank \code{k = 6}. See
-#' the vignette how the Poisson NMF model fitting was performed.}
+#' the vignette how the Poisson NMF model fitting was performed.}}
 #'
-#' \item{de}{Result of calling 
-#' \code{de_analysis(fit,counts,pseudocount = 0.1,
-#' control = list(ns = 1e4,nc = 4))}
-#' after first setting the seed to 1, \code{set.seed(1)}.}}
-#'
-#' @source
 #' \url{https://www.10xgenomics.com/resources/datasets}
 #' 
 #' @references

vignettes/single_cell_rnaseq_basic.Rmd

@@ -268,9 +268,14 @@ de <- de_analysis(fit,counts,pseudocount = 0.1,
 
 Since this computation can take 10 minutes or more to run, we have
 provided the output of this `de_analysis` call in the `pbmc_facs` data
-set:
+set. Since the `de_analysis` output is quite large, we have made this
+available outside the package:
 
 ```{r de-analysis-2}
+pbmc_facs_file <- tempfile(fileext = ".RData")
+pbmc_facs_url <- "https://stephenslab.github.io/fastTopics/pbmc_facs.RData"
+download.file(pbmc_facs_url,pbmc_facs_file)
+load(pbmc_facs_file)
 de <- pbmc_facs$de
 ```
 

vignettes/single_cell_rnaseq_practical.Rmd

@@ -194,10 +194,15 @@ More on differential expression analysis
 ----------------------------------------
 
 In [Part 1][vignette-part-1], we performed a DE analysis using the
-topic model.
+topic model. (Note that since the `de_analysis` output is quite large,
+we have made the results of the DE analysis available outside the
+package.)
 
 ```{r diff-count-analysis}
-de <- pbmc_facs$de
+pbmc_facs_file <- tempfile(fileext = ".RData")
+pbmc_facs_url <- "https://stephenslab.github.io/fastTopics/pbmc_facs.RData"
+download.file(pbmc_facs_url,pbmc_facs_file)
+load(pbmc_facs_file)
 ```
 
 When the volcano plot shows many overlapping differentially expressed