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Error message when running FindMotifs() #223

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chent5 opened this issue Sep 9, 2020 · 2 comments
Closed

Error message when running FindMotifs() #223

chent5 opened this issue Sep 9, 2020 · 2 comments
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bug Something isn't working

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@chent5
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chent5 commented Sep 9, 2020

Hi Tim,

Thanks a lot for developing this very useful package.

I got an error message when running the code below:

enriched.motifs <- FindMotifs(
    object = signac.object,
    features = da.list[[i]]
  )

Here is the error message: "Testing motif enrichment in 265 regions
Error in smooth.spline(lambda, pi0, df = smooth.df) :
missing or infinite values in inputs are not allowed".

Actually, I used a loop to do motif enrichment for a list of differential accessible peaks. Each list element contains a vector of the DA peaks for a specific cluster. The error only occurs in a specific loop but not all.

I googled this error and I found this link https://support.bioconductor.org/p/105623/
It seems something wrong happens when computing q value. Is there any way to bypass this error or computing q value? I can compute adjusted p-value later after I get all the motif enrichment results.

@chent5 chent5 added the bug Something isn't working label Sep 9, 2020
@timoast
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timoast commented Sep 9, 2020

It looks like when there are a lot of p-values close to zero, qvalue has trouble estimating pi0. Since this can often happen when finding enriched motifs, and it's easy for users to compute adjusted p-values themselves using whatever method they prefer, I have removed the qvalue calculation (0a3b4de). This is currently available on the develop branch

@cacaonib
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It looks like when there are a lot of p-values close to zero, qvalue has trouble estimating pi0. Since this can often happen when finding enriched motifs, and it's easy for users to compute adjusted p-values themselves using whatever method they prefer, I have removed the qvalue calculation (0a3b4de). This is currently available on the develop branch

really sorry. i watched 0a3b4d. but i can't understand that how apply in my R environment. please explicate this command and work flow in detail thank you

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