Delete run_deseq.R

src/run_deseq.R

-library("DESeq2")
-
-directory <- "mydatalocal/counts_simulation/results/"
-
-
-sampleFiles <- grep("*tsv",list.files(directory),value=TRUE)
-sampleName <- sub("*.tsv","",sampleFiles)
-
-sampleName
-
-sampleCondition <- as.character(sampleName)
-for (i in 1:length(sampleCondition)){
-  sampleCondition[i] <- gsub("_[A-B]", "", sampleCondition[i])
-}
-
-
-sampleCondition
-
-sampleTable <- data.frame(sampleName = sampleName,
-                          fileName = sampleFiles,
-                          condition = sampleCondition)
-sampleTable
-str(sampleTable)
-
-ddsInput <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable,
-                                       directory = directory,
-                                       design = ~ condition)
-
-
-
-dds <- DESeq(ddsInput)
-
-resultsNames(dds)
-
-resLFC <- lfcShrink(dds, coef=2, type="apeglm")
-resLFC
-# an alternate analysis: likelihood ratio test
-ddsLRT <- DESeq(dds, test="LRT", reduced= ~ 1)
-resLRT <- results(ddsLRT)
-resLRT
-
-
-dds$sizeFactor*(res$log2FoldChange)
-
-coef(dds)
-coef(dds, SE=TRUE)[1,]
-
-dds <- estimateSizeFactors(dds)
-dds$condition
-head(counts(dds, normalized=TRUE))
-
-resGA <- results(dds, contrast=c("condition","env1","env2"), lfcThreshold=.4, altHypothesis="greaterAbs")
-table(resGA$padj < 0.05)
-
-
-
-########################" poUR ALLER CHERHCERH DES TRUC INTERESSANT
-## simulation functions
-source("mydatalocal/counts_simulation/src/simulators.R")
-
-var(rnbinom(10000, mu=1000, size=200))
-
-
-N_gene= 6000
-N_cond= 2
-N_rep= 2
-
-
-mtrx<-matrix_generator(1000, 2)
-cond <- factor(rep(1:2, each=N_rep))
-dds <- DESeqDataSetFromMatrix(cnts, DataFrame(cond), ~ cond)
-
-# standard analysis
-dds <- DESeq(dds, fitType='local')
-res <- results(dds)
-
-mcols(dds,use.names=TRUE)[1:4,]
-substr(names(mcols(dds)),1,10) 
-mcols(mcols(dds), use.names=TRUE)[1:4,]
-assays(dds)[["mu"]]
-
-head(assays(dds)[["mu"]][which(res$padj<0.05),])
-
-head(assays(dds)[["mu"]][which(res$padj>0.05),])
-
-dispersions(dds)
-
-assays(dds)[["cooks"]][27,]
-
-sizeFactors(dds)
-b =mcols(dds)
-assays(dds)[["H"]]
-
-
-alpha_sample = dispersions(dds)
-