Normally, when we use RNA-seq data,in the results, we can say some coding genes are up-regulated or some are down-regulated, so product (proteins) will be affected based on this activity. So in principle this analysis is called as DEGs. I hope I correctly explained this phenomenon. Basically, we count the mapped reads against coding part of genome to get that information before performing DEGs.
What about Metagenome ? We have some abundances of proteins in the functional annotation part (GO, Pfam, KEGG, or so on). When we compare the different samples from different location, how should we interpret the result ?
OK, I will give more concrete example. Eg, considering Gene Ontologies
GO category: response to abiotic stimulus
Sample A abundance: 20, Sample B abundance: 50, Sample C abundance : 20
If it is RNA-seq count, I would say Sample B have the genes which belong to "response to abiotic stimulus" are differentially expressed and my inference is that sample B encounter a different abiotic stress than other samples.
What about in metagenome results ? How to interpret or how not to interpret ?
Thank you in advance.