maSigPro RNAseq data (counts=TRUE will not work for negative binomial)
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@guest-user-4897
Last seen 9.6 years ago
Dear List, I really need help with this. I am in the middle of writing a manuscript and need this data. Basically I have a matrix of counts (data) made up of large counts without decimal points. I also have my edesign object with the Group column filled with all 1's since I am trying to do single series time course analysis. The design matrix and everything turn out fine. However, when I try to use p.vector with counts=TRUE, I get this error: fit=p.vector(data, design, counts=TRUE, min.obs=0) Error in if (model.glm$null.deviance == 0) { : missing value where TRUE/FALSE needed I have tried this so many different ways and cannot figure out how to correct the error. Please help. Audra -- output of sessionInfo(): > sessionInfo() R version 3.0.2 (2013-09-25) Platform: x86_64-apple-darwin10.8.0 (64-bit) locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] tcltk parallel stats graphics grDevices utils datasets methods base other attached packages: [1] maSigPro_1.34.0 DynDoc_1.40.0 widgetTools_1.40.0 MASS_7.3-29 Biobase_2.22.0 [6] BiocGenerics_0.8.0 loaded via a namespace (and not attached): [1] limma_3.18.13 Mfuzz_2.20.0 tkWidgets_1.40.0 tools_3.0.2 -- Sent via the guest posting facility at bioconductor.org.
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@ma-jose-nueda-2304
Last seen 3.4 years ago
Spain
Hi Audra, This error is due to there are some case with a lot of zeros. Before applying maSigPro, these data must be removed. And remember that data must be normalized. Regards, Mar?a J. Nueda -----Mensaje original----- From: Audra Andrew [guest] Sent: Saturday, March 08, 2014 12:37 AM To: bioconductor at r-project.org ; audra.loy at mavs.uta.edu Subject: [BioC] maSigPro RNAseq data (counts=TRUE will not work for negativebinomial) Dear List, I really need help with this. I am in the middle of writing a manuscript and need this data. Basically I have a matrix of counts (data) made up of large counts without decimal points. I also have my edesign object with the Group column filled with all 1's since I am trying to do single series time course analysis. The design matrix and everything turn out fine. However, when I try to use p.vector with counts=TRUE, I get this error: fit=p.vector(data, design, counts=TRUE, min.obs=0) Error in if (model.glm$null.deviance == 0) { : missing value where TRUE/FALSE needed I have tried this so many different ways and cannot figure out how to correct the error. Please help. Audra -- output of sessionInfo(): > sessionInfo() R version 3.0.2 (2013-09-25) Platform: x86_64-apple-darwin10.8.0 (64-bit) locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] tcltk parallel stats graphics grDevices utils datasets methods base other attached packages: [1] maSigPro_1.34.0 DynDoc_1.40.0 widgetTools_1.40.0 MASS_7.3-29 Biobase_2.22.0 [6] BiocGenerics_0.8.0 loaded via a namespace (and not attached): [1] limma_3.18.13 Mfuzz_2.20.0 tkWidgets_1.40.0 tools_3.0.2 -- Sent via the guest posting facility at bioconductor.org. _______________________________________________ Bioconductor mailing list Bioconductor at r-project.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
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ipiras • 0
@ipiras-9581
Last seen 4.1 years ago

Hello,

did u fix the error?

I found the same error with the function T.fit, using normalized counts for 3 samples (time course experiment for 1 condition).

I normalized the count with deseq2:

dds2 <- estimateSizeFactors(ddsMat)
ddsNorm <- counts(dds2, normalized=TRUE) 

[.....]

The first steps work properly but when I arrive at:

NBt <- T.fit(NBp)
Error in if (group != indepen) { : missing value where TRUE/FALSE needed

I read this thread and I filtered my dataset to remove 0 values (also using "crazy" values to be sure to remove them), but I get the same error. Any suggestion? Has the function been tested also for time course experiment with 1 condition?

Thank you very much in advance for any help.

I.

 

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jariani.abb ▴ 10
@jarianiabb-9953
Last seen 6.6 years ago

Hi,

I had the same issue and I had normalized my data already with cuffnorm. The answer from Maria Nueda pointed me to the solution. I removed the rows (genes) who have zero for all time points:

 

>fit0 <- p.vector(glurep_data_FPKM, design, counts = TRUE,min.obs=10)

Error in if (model.glm$null.deviance == 0) { : 
  missing value where TRUE/FALSE needed

 

>glurep_data_FPKM_nz <- glurep_data_counts[ rowSums(glurep_data_counts)!=0, ] 
>fit <- p.vector(glurep_data_FPKM_nz, design, counts = TRUE,min.obs=10) 

 

and it worked.

 

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