I am currently working on 16 bulk RNAseq samples. I did some basic research on statistical testing of differential expression and figured out two R packages to edgeR and DESeq2.
The 16 samples are actually paired samples data from before treatment and after treatment from 8 patients. I am interested in finding DE genes within paired samples for instance (P1_AT vs P1_BT). This is the design matrix
Sample Patient Time P1_BT P1 BT P1_AT P1 AT P2_BT P2 BT P2_AT P2 AT ........ P8_BT P8 BT P8_AT P8 AT
So I have created my design matrix like section 4.1
design <- model.matrix(~ Patient+Treatment)
EdgeR manual, my experiment design is exactly similar to section 4.1 of edgeR manual.
But I am interested in getting 1) P1_AT vs P1_BT, 2) P2_AT vs P2_BT ... 8) P8_AT vs P8_BT
To find genes with baseline differences between the drug and the placebo at 0 hours: qlf <- glmQLFTest(fit, contrast=my.contrasts[,"DrugvsPlacebo.0h"]) my.contrasts <- makeContrasts( + Drug.1vs0 = Drug.1h-Drug.0h, + Drug.2vs0 = Drug.2h-Drug.0h, + Placebo.1vs0 = Placebo.1h-Placebo.0h, + Placebo.2vs0 = Placebo.2h-Placebo.0h, + DrugvsPlacebo.0h = Drug.0h-Placebo.0h, + DrugvsPlacebo.1h = (Drug.1h-Drug.0h)-(Placebo.1h-Placebo.0h), + DrugvsPlacebo.2h = (Drug.2h-Drug.0h)-(Placebo.2h-Placebo.0h), + levels=design)
The design matrix is different for section 4.1 and section 3.3.1. My experiment similar to section 4.1, so I have used that design matrix. But I want the results of section 3.3.1 within samples comparison.
Any comments are appreciated.