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I have a question regarding transcription factor (TF) activity analysis in bulk RNA-seq. In my analysis, I used lfcShrink() instead of results() for differential expression analysis to reduce noise in my in vitro data. However, I noticed that when using 'apeglm' for effect size estimation, the 'stat' value is not available.
Given this, which value would you recommend using as a substitute for 'stat' in this context?
I have attached the DESeq2 output, hope it helps clarify my question.
Hello,
Thank you for providing such amazing tools!
I have a question regarding transcription factor (TF) activity analysis in bulk RNA-seq. In my analysis, I used lfcShrink() instead of results() for differential expression analysis to reduce noise in my in vitro data. However, I noticed that when using 'apeglm' for effect size estimation, the 'stat' value is not available.
Given this, which value would you recommend using as a substitute for 'stat' in this context?
I have attached the DESeq2 output, hope it helps clarify my question.
Looking forward to your insights!
Best regards,
Yaqin
DESeq2 output.xlsx
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