Please forgive my ignorance. I am a novice in tinkering with RNAseq or bioinformatics.
I have read a few posts suggesting to follow standard pipelines for analyzing DEGs in a given experiment.
However, I am not in possession of the raw data, and have been given only file containing TPM. I have been told to do a t-test, adjust for multiple testing, and filter for DEGs from this list.
a) Is this a valid approach?
b) I have read that for microarray data, first log2 transformed and then analysis for DEGs. Can a similar approach be taken in my situation? My concern is that there are several (many) rows where 50% of TPM values are 0. Would it be wise to remove these rows?
c) if t-test suffices, and log2 transformation is not required, do I acquire LogFC values as: mean(log2(test))-mean(log2(control))?
If a similar question has already been asked, please feel free to disregard. I'm still going through the forums to try and figure out what is the best approach (in my case).