ddsFullCountTable <- DESeqDataSetFromMatrix(countData = mouse_count, colData = mouse_pheno, design = ~ batch + age + gender + treatment) dds <- DESeq(ddsFullCountTable, test="LRT", reduced = ~ batch + age + gender) res_dds <- results(dds, contrast = c("treatment", "med", "ck")) summary(res_dds) # out of 32102 with nonzero total read # adjusted p-value < 0.1 # LFC > 0 (up) : 0, 0% # LFC < 0 (down) : 0, 0% # outliers  : 1269, 3.6% # low counts  : 0, 0% # (mean count < 0) #  see 'cooksCutoff' argument of ?results #  see 'independentFiltering' argument of ?results
Here are 5 med mice and 7 check mice (so the ncols is 12 for countData) RNA-Seq data be used to do DE analysis, to find the DEGs affected by medicine, but seems no genes. This problem has confused me for a long time, I checked and tired many times, still haven't been solved. As far as I understand it, I guess:
- Too few samples (and too many covariates?)?
- The drug not statistically significant in this case?
- The code, I guess not?
Or other problems?