I am using Kallisto and Sleuth for analysis of RNA-seq data.
When doing differentially analysis, I first run a LRT test in Sleuth (which compares the likelihood of the data assuming no differential expression (null model) against the likelihood of the data assuming differential expression (alternative model)). I then run a Wald test (which tests only one model and reports differential expression).
I then find a list of loci that have passed both the LRT and Wald tests (q value<0.05).
However, I fail to find any loci that pass the LRT test. Conversely, their are >2000 loci that pass the Wald's test.
For analysis of RNA-seq data, would it be okay to only look at Wald-passed LRT-failed data?
Conversely, for some experiments, I have a list of loci that pass both LRT and Wald? Are both Wald-passed LRT-passed, and Wald-passed LRT-passed data both equally valid for publication?
LRT is more stringent, I suppose, so would it be the case that if replicates are quite variable, then we will see fewer loci that pass the LRT test?