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Merge pull request #634 from PatrickDeelen/master
Recount3 scripts and new release for genotype harmonizer
2 parents 028213b + 887cd41 commit 9300129

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.gitignore

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.Rproj.user
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.Rhistory
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/DEPICT2/src/main/r/downstreamer_main/downstreamer_main.Rproj
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Downstreamer/src/main/r/downstreamer_main/.remoterserverlog

Downstreamer/pom.xml

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<version>1.0.4-SNAPSHOT</version>
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</parent>
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<artifactId>Downstreamer</artifactId>
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<version>1.29-SNAPSHOT</version>
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<version>1.30-SNAPSHOT</version>
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<packaging>jar</packaging>
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<build>
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<resources>
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Version: 1.0
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RestoreWorkspace: Default
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SaveWorkspace: Default
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AlwaysSaveHistory: Default
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EnableCodeIndexing: Yes
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UseSpacesForTab: Yes
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NumSpacesForTab: 2
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Encoding: UTF-8
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RnwWeave: Sweave
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LaTeX: pdfLaTeX

Downstreamer/src/main/r/downstreamer_main/legacy_scripts/combineAnnotations.R

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combinedMeta$Cancer[studySamples] <- FALSE
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#SRP081020 is mis-anotated in SRA as PBMC, paper and clustering both state wholeblood
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studySamples <- combinedMeta$study %in% c("ERP114104", "SRP051848", "SRP056784", "SRP071965", "SRP077975", "SRP081020", "SRP098758", "SRP113245", "SRP126580", "SRP126582", "SRP126583", "SRP136057", "SRP144583", "SRP150872", "SRP214077")
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studySamples <- combinedMeta$study %in% c("ERP114104", "SRP051848", "SRP056784", "SRP071965", "SRP077975", "SRP081020", "SRP098758", "SRP113245", "SRP126580", "SRP126582", "SRP126583", "SRP136057", "SRP144583", "SRP150872", "SRP214077", "SRP056443")
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combinedMeta$Tissue[studySamples] <- ""
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combinedMeta$Tissue2[studySamples] <- ""
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combinedMeta$Cellline[studySamples] <- NA
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combinedMeta$Cellline[!is.na(combinedMeta$CelllineName)&combinedMeta$CelllineName=="iPSC"] <- TRUE
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combinedMeta$Cancer[!is.na(combinedMeta$Cellline) & combinedMeta$Cellline] <- NA
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#save(combinedMeta, file = "combinedMeta_2022_09_02.RData")
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#save(combinedMeta, file = "combinedMeta_2022_09_15.RData")
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load(file = "combinedMeta_2022_08_19.RData")
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setwd("D:\\UMCG\\Genetica\\Projects\\Depict2Pgs")
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source(paste0("C:\\Users\\patri\\Documents\\GitHub\\systemsgenetics\\Downstreamer\\src\\main\\r\\downstreamer_main/downstreamer_functions.r"))
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traits <- read.delim("MetaBrain/traits.txt")
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i <- 1
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pdf("MetaBrain/withAndWithoutEqtls.pdf", height = 20, width = 10)
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#png("MetaBrain/withAndWithoutEqtls.png", height = 2000, width = 1000)
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layout(matrix(1:8, ncol =2))
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par(pty="s")
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for(i in 1:nrow(traits)){
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trait <- traits[i, "trait"]
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name <- traits[i, "name"]
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enrichments <- read.depict2(paste0("MetaBrain/normal/",trait,"_enrichtments.xlsx"))$GenePrioritization_MetaBrain
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enrichmentsIncEqtl <- read.depict2(paste0("MetaBrain/inceqt/",trait,"_enrichtments.xlsx"))$GenePrioritization_MetaBrain
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enrichmentsBoth <- merge(enrichments, enrichmentsIncEqtl, "Gene.ID" , suffixes= c("Normal", "incEqtl"))
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maxZ <- max(range(enrichmentsBoth$Enrichment.Z.scoreNormal, enrichmentsBoth$Enrichment.Z.scoreincEqtl))
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r <- cor(enrichmentsBoth$Enrichment.Z.scoreNormal, enrichmentsBoth$Enrichment.Z.scoreincEqtl)
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plot(enrichmentsBoth$Enrichment.Z.scoreNormal, enrichmentsBoth$Enrichment.Z.scoreincEqtl, bg = adjustcolor("dodgerblue2", alpha.f = 0.3), pch = 21, col=adjustcolor("dodgerblue2", alpha.f = 0.5), asp = 1, xlab = "Key gene score without eqtl information", ylab = "Key gene score without eqtl information", xlim = c(-maxZ,maxZ), ylim = c(-maxZ,maxZ), main = name)
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mtext(paste0("Pearson r: ", signif(r,2)))
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}
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dev.off()

Downstreamer/src/main/r/downstreamer_main/legacy_scripts/playingWithPcaSvd.R

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abline(v=60)
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library(rpca)
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expRpca <- rpca(t(expSub2))
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library(corpcor)
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expSvdFast <- fast.svd(expSubScale)

Downstreamer/src/main/r/downstreamer_main/legacy_scripts/recount3/umap.R

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