Hi, I have dataset with transcripts from 3 population in 3 treatments and 2 replicates, totaling 18 samples.
The aims of this analysis are:
- Identify differentially expressed genes (DEGs) between pairs of treatments for each population
- Identify DEGs between populations
DESeq model ~ population + treatments + population : treatments
PCA
The variation within population in similar in all three, however some treatments cluster for one species but does not in another i.e. the two crowding and the two low nutrient samples cluster well in the progenitor and only one of these clusters in domesticated and wild. This clustering in the progenitor would make it easier to pick up differentially expressed genes between pairs of treatments.
I'm just wondering if it is possible to standardise the data so that there is the same variation between treatments for each population, to make identifying DEGs between populations more comparable.
Hope someone can help :) Thanks
Looks like you are using DESeq2 for your data analysis. What do you think DESeq2 normalization do to your data? Why would you not allow the data talk by itself? Your data is under powered, your replicates are on the low side. Usually, the low powered studies suffer from an increased chance of false positives. However, your study is technically OKAY and should be fine for hypothesis generation.