Question: high fold changes due to the low counts
1
gravatar for tonja.r
4.3 years ago by
tonja.r460
UK
tonja.r460 wrote:

I computed log2 fold changes (which is normally distributed)  of treated vs untreated. I standartized ((x-mean)/sd) it and computed the p-values based on the assumption of the normal distribution and z-scores.  I got some quite high log2 fold changes mainly due to the low counts. Is there a possibility to account for the low-counts (e.g high counts) while computing fold changes or to model the log 2 fold change as another distribution ( like beta distribution) that will count for the low-counts?


(PS. I am aware of DESeq, GFOLD, edgeR. However, I need a simple (maybe not that robust and reliable) method to account for low counts while calculating the p-values)

rna-seq • 1.3k views
ADD COMMENTlink modified 4.1 years ago by jianxing.tongji30 • written 4.3 years ago by tonja.r460
1
gravatar for jianxing.tongji
4.1 years ago by
jianxing.tongji30 wrote:

A reasonable model like DESeq, GFOLD or edgeR should not be cursed by low read counts. The calculation is not related to fold change.

ADD COMMENTlink written 4.1 years ago by jianxing.tongji30
0
gravatar for jianxing.tongji
4.1 years ago by
jianxing.tongji30 wrote:

A reasonable model like DESeq, GFOLD or edgeR should not be cursed by low read counts. The calculation is not related to fold change.

ADD COMMENTlink written 4.1 years ago by jianxing.tongji30
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