Question: Orthogonal regression (edgeR, DESeq, limma or others)?

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Panos Bolan •

**20**wrote:Dear list,
I am a postdoc in Bioinformatics, working on gene/gene regulation
using RNA-seq data. I would like to find the associations for a set of
gene pairs that my collaborator sent me. I have 1000 such pairs whose
counts are measured for 400 samples. One way to do it would be by
simple correlations (Spearman CPMs) or by using limma (faster than
edgeR and DESeq for this task) and model the voom-transformed data as
Gene1 ~ Gene2.
The problem I see with the 'correlations' solution is that it's a very
simple model that does not take into account the dispersion of the
data, while 'lima' or edger or other would possibly give different
answers for Gene1 ~ Gene2 and Gene2 ~ Gene1, so it would be confusing
if I wanted to estimate a bootstrap P-value of significance.
I would like to ask if there is any model that uses orthogonal
regression for RNA-seq data (assuming that all measurements come with
error and that the error variances are equal).
Thank you,
Pan
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modified 4.9 years ago
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Gordon Smyth ♦

**36k**• written 4.9 years ago by Panos Bolan •**20**