I have done Differential analysis by using edge R in. R studio. I have done all the test required for this method. I have also adjusted p values. Now, I am at a stage where I am doing the visulization of the data for manuscript. Upregulated gene are 25000 and downregulated genes are 2000 and its seems overwhelming to perform DAVID and PPI analysis. So, what should I can do for thus condition? Can I retreive the top 200/300 genes from the trear table and perform all the visulization. Kinldly give me suggestions as I am stuck in the middle of my work and there is no one around me to give me any suggestions. Thanks.
25000 upregulated genes, is this a typo? That is basically impossible to have 25k DEGs.
In any case, you can start by setting a minimal fold change or more stringent padj. edgeR has a
glmTreat
function that the authors recommend to narrow down DEGs with respect to a minimal fold change.sorry it was typo mistake. it is 2500 and I am using lfc=1.5 and p.adjusted 0.05. what you suggest in this scenario. Thanks
If you feel that this is too many genes make p.adjust more stringent, or use glmTreat will prioritize genes relative to the fold change cutoff you used.
Thanks. One more thing I want to clarify. After applying glmtreat with log fc = 2, now upregulated genes become 1500. Can I look on just top 200/ 500 and then apply further analysis? because whenever I read articles people are mentioning very less number of DEG genes around 200 or 300 and I am bit confused that how it is possible as I have done all the way which makes genes to let it narrow. Kindly give me your suggestion . Thanks