Hi
for differential gene expression analysis do we take account only all the common transcripts across the samples or else, we take all the transcripts present in all samples ? please some comments!
•
written
by
sunnykevin97
1 answer
Hello sunnykevin97,
It can be accepted that some genes / transcripts will have expression values of 0 (zero) in some samples, which may be encoded as NA, depending on your upstream pipeline. There is no justification to remove a gene / transcript that has a value of 0 / NA in just one sample, though.
What you can do is one or both of the following prior to normalisation:
- remove genes / transcripts that have a low mean across all samples
- remove genes / transcripts that have a high rate of being 0 / NA across all samples
If you would like further help, then please be very specific about the programs and methods that you are using so as to avoid confusion and a lengthy thread.
Kevin
Log in to answer this question.
-
RNAseq meta-analysis to identify “consistently expressed” genes
written by cgibbsm •
-
DE analysis with multiple factors
written by Abhishek •
-
Differential expression pattern of known miRNAs
written by Rey •
-
What are the reasons to find so few Differentially expressed genes (DEGs)?
written by sunnykevin97
-
Gene starts with "LOC" prefix ?
written by sunnykevin97
-
How important is normalization for RNA_Seq data ?
written by sunnykevin97
-
Transcript quantification/Differential gene expression analysis ?
written by sunnykevin97
-
Correlation vs differential expression testing
written by prabin.dm
-
Why are transcripts of a same gene expressed differently in same samples?
written by ngs101.com
-
pvalues as features in SVM classifier
written by Marouen Ben Guebila •
