Hi all,
I have to analyze RNAseq data concerning 4 different tissues. I have biological replicates.
Until now, I did pairwise DE analyses using edgeR and I got the Differntially Expressed genes for each comparison, with p-values and FDR.
Now, I would like to look at the condition-specific genes but I am not sure about the way to get them...
I can either start from the different fold-changes in the different pairwise comparisons and try to get the conditions were a gene is the most expressed, but it is quite complicated.
I also tried to cluster the genes (after sequencing depths normalizations) but then I have the problem of genes which are not expressed at all (0 counts) in some tissue.
I looked at some R packages like SpeCond but this one was done for microarrays so the quantification distribution is quite different and I do not think we can apply the same statistical model.
How do you do?
Thanks in advance...
I have to analyze RNAseq data concerning 4 different tissues. I have biological replicates.
Until now, I did pairwise DE analyses using edgeR and I got the Differntially Expressed genes for each comparison, with p-values and FDR.
Now, I would like to look at the condition-specific genes but I am not sure about the way to get them...
I can either start from the different fold-changes in the different pairwise comparisons and try to get the conditions were a gene is the most expressed, but it is quite complicated.
I also tried to cluster the genes (after sequencing depths normalizations) but then I have the problem of genes which are not expressed at all (0 counts) in some tissue.
I looked at some R packages like SpeCond but this one was done for microarrays so the quantification distribution is quite different and I do not think we can apply the same statistical model.
How do you do?
Thanks in advance...
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