$VAR1 = {
          'uninfected' => [
                            'uninfected_01',
                            'uninfected_02',
                            'uninfected_03',
                            'uninfected_04',
                            'uninfected_05',
                            'uninfected_06'
                          ],
          'infected' => [
                          'infected_01',
                          'infected_02',
                          'infected_03',
                          'infected_04',
                          'infected_05',
                          'infected_06',
                          'infected_07',
                          'infected_08',
                          'infected_09',
                          'infected_10',
                          'infected_11',
                          'infected_12',
                          'infected_13',
                          'infected_14',
                          'infected_15',
                          'infected_16',
                          'infected_17',
                          'infected_18'
                        ]
        };
CMD: R --no-save --no-restore --no-site-file --no-init-file -q < salmon.gene.counts.matrix.infected_vs_uninfected.infected.vs.uninfected.EdgeR.Rscript
> if (! require(edgeR)) {
+    source("https://bioconductor.org/biocLite.R")
+    biocLite("edgeR")
+    library(edgeR)
+ }
> 
> data = read.table("/gscratch/scrubbed/samwhite/outputs/20200422_cbai_DEG_basic_comparisons/infected-uninfected/salmon.gene.counts.matrix", header=T, row.names=1, com='')
> col_ordering = c(2,3,4,5,6,7,10,11,12,13,14,15,16,19,20,21,22,23,1,8,9,17,18,24)
> rnaseqMatrix = data[,col_ordering]
> rnaseqMatrix = round(rnaseqMatrix)
> rnaseqMatrix = rnaseqMatrix[rowSums(cpm(rnaseqMatrix) > 1) >= 2,]
> conditions = factor(c(rep("infected", 18), rep("uninfected", 6)))
> 
> exp_study = DGEList(counts=rnaseqMatrix, group=conditions)
> exp_study = calcNormFactors(exp_study)
> exp_study = estimateDisp(exp_study)
Design matrix not provided. Switch to the classic mode.
> et = exactTest(exp_study, pair=c("infected", "uninfected"))
> tTags = topTags(et,n=NULL)
> result_table = tTags$table
> result_table = data.frame(sampleA="infected", sampleB="uninfected", result_table)
> result_table$logFC = -1 * result_table$logFC
> write.table(result_table, file='salmon.gene.counts.matrix.infected_vs_uninfected.edgeR.DE_results', sep='	', quote=F, row.names=T)
> write.table(rnaseqMatrix, file='salmon.gene.counts.matrix.infected_vs_uninfected.edgeR.count_matrix', sep='	', quote=F, row.names=T)
> source("/gscratch/srlab/programs/trinityrnaseq-v2.9.0/Analysis/DifferentialExpression/R/rnaseq_plot_funcs.R")
> pdf("salmon.gene.counts.matrix.infected_vs_uninfected.edgeR.DE_results.MA_n_Volcano.pdf")
> plot_MA_and_Volcano(rownames(result_table), result_table$logCPM, result_table$logFC, result_table$FDR)
> dev.off()
null device 
          1 
>