I wanted some advice on the way I am planning on analyzing my samples in terms of if it's done properly and if statistically sound.
My biological question is: What is common between human and mouse cancer cell lines in how they deal with Vaccinia infection in terms of transcriptional changes?
If I was interested in a human cancer cell specific response, I could use any number of tools such as cuffdiff or ballgown, but I want what is common and that's difficult because both mouse and human species have different genomes and annotations. I could do separate comparisons, human uninfected vs infected and mouse infected vs infected and then take what's common, but I want to try and do one comparison.
My experimental samples is 5 different human cancer cell lines, uninfected and infected with virus, no replicates, 10 samples total. I also have 5 different mouse cancer cell lines, uninfected and infected with virus, no replicates, 10 samples. I did not do replicates per condition as I am not interested in cell lines specific differences, rather I want an overall response to viral infection common for all cell line models.
I am planning on: 1. Map human samples to human genome, mouse samples to mouse genome and get bam files. 2. Use featureCounts on both human and mouse samples to get read counts mapping per protein coding gene for both species. 3. Merge human and mouse counts and only keep genes that have the same name between mouse and human species. 4. Feed those counts to DESeq2 and do my comparison with that package, all Uninfected vs all Infected.