Recently I got some RNA-seq data for differential expression analysis. Because there is no biological rep, I tried different software, edgeR, DESeq and DEGseq, and they came with different results.
For edger: I got about 8000 DEGs based on the scripts in mannual and filtered by LogFC>1 and <-1.
For DEGseq: I got about 7000 DEGs based on the the scripts in mannual and and filtered by LogFC>1 and <-1, the method used is MARS.
For DESeq: I only got about 250 DEGs based on padj<0.05.
There is so big difference using different softwares, for edger and DEGseq, they came with too much genes I expected, and for DESeq, it came with too little genes I expected. The old question came to me again: which method is good for analyze RNA-seq data for DEGs without biological replicates? Is anyone can summary the standard to filter genes by different softwares? Or whether Fisher's exact test (R build-in function) works better for data without biological replication?
I just began to learn how to do the analysis, and it is quite new to me. I will appreciate very much for any suggestions.
-
Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?
Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating...10-14-2026, 09:55 AM