Hi, I am working on RNA-Seq data for Arabidopsis plant. I have samples from 4 genotypes (A, B, C, D), Untreated and after treatment, with 3 replicates for each. I used STAR for alignment and obtained count.txt file by using featureCounts. Now I am doing the DGE analysis by DESeq2. My coldata looks like this:
genotype treatment A.1_Control A Mock A.2_Control A Mock A.3_Control A Mock A.1_PostDL A Post-HL A.2_PostDL A Post-HL A.3_PostDL A Post-HL B.1_Control B1 Mock B.2_Control B1 Mock B.3_Control B1 Mock B.1_PostDL B1 Post-HL B.2_PostDL B1 Post-HL B.3_PostDL B1 Post-HL C.1_Control C Mock C.2_Control C Mock C.3_Control C Mock C.1_PostDL C Post-HL C.2_PostDL C Post-HL C.3_PostDL C Post-HL D.1_Control D Mock D.2_Control D Mock D.3_Control D Mock D.1_PostDL D Post-HL D.2_PostDL D Post-HL D.3_PostDL D Post-HL
I am using this code for analysis:
countdata <- read.table("NewTotalCounts.txt", header=TRUE, row.names=1) countdata <- countdata[ ,6:ncol(countdata)] colnames(countdata) <- gsub("\\.[sb]am$", "", colnames(countdata)) countdata <- as.matrix(countdata) library(DESeq2) dds <- DESeqDataSetFromMatrix(countData=countdata, colData=coldata, design=~genotype*treatment) dds dds <- DESeq(dds) matrix(resultsNames(dds)) "1" "Intercept" "2" "genotype_C_vs_A" "3" "genotype_D_vs_A" "4" "genotype_B_vs_A" "5" "treatment_Post.HL_vs_Mock" "6" "genotypeC.treatmentPost.HL" "7" "genotypeD.treatmentPost.HL" "8" "genotypeB.treatmentPost.HL"
I extracted the DE genes for each contrast as:
> res_C <- results(dds, contrast="genotype_C_vs_A", alpha=0.05, lfcThreshold=0) > summary(res_C) out of 27683 with nonzero total read count adjusted p-value < 0.05 LFC > 0 (up) : 115, 0.42% LFC < 0 (down) : 107, 0.39% outliers  : 2, 0.0072% low counts  : 6909, 25% (mean count < 4)  see 'cooksCutoff' argument of ?results  see 'independentFiltering' argument of ?results
I am generating the VennDiagram as:
venn(list(B_vs_A=rownames(res_B[which(res_B$padj <= 0.05),]), C_vs_A=rownames(res_C[which(res_C$padj <= 0.05),]), D_vs_A=rownames(res_D[which(res_D$padj <= 0.05),])))
My questions are:
I am not able to understand the contrasts it is making like; contrast "genotype_C_vs_A" is under Mock condition or after treatment; what is "treatment_Post.HL_vs_Mock" - it is for which sample, and "genotypeC.treatmentPost.HL" - it is after treatment vs A or vs C(Mock) ?
How can I extract these DE genes?
How can I extract the DE genes which are common in two or all the contrasts?
Any help from you will be very helpful for me. Thank you