Hello,
I'm working with a data set that we have yet to replicate. I'm trying to take a cursory look at the differential expression, but I keep getting an error I don't understand. I don't know if it matters but I'm generating my count tables with HTSeq. Here is the error:
> table = read.delim(file="~/neuron_rna_seq/hypodermis_table.txt", header=FALSE, stringsAsFactors=TRUE)
> cds = newCountDataSetFromHTSeqCount(table, directory="~/neuron_rna_seq")
> cds = estimateSizeFactors( cds )
> sizeFactors( cds )
hypodermis hypodermis_unfiltered
0.3333333 3.0000000
> cds = estimateDispersions(cds, method="blind", sharingMode="fit-only")
Error in parametricDispersionFit(means, disps) :
Parametric dispersion fit failed. Try a local fit and/or a pooled estimation. (See '?estimateDispersions')
In addition: Warning message:
glm.fit: algorithm did not converge
#Because of this I use the local fit
> cds = estimateDispersions(cds, method="blind", sharingMode="fit-only", fitType="local")
> results = nbinomTest(cds, "hypodermis", "hypodermis_unfiltered")
#Error in question
Error in if (dispTable(cds)[condA] == "blind" || dispTable(cds)[condB] == :
missing value where TRUE/FALSE needed
I apologize if this is a basic question, I'm not an experienced user.
Thanks!
April
I'm working with a data set that we have yet to replicate. I'm trying to take a cursory look at the differential expression, but I keep getting an error I don't understand. I don't know if it matters but I'm generating my count tables with HTSeq. Here is the error:
> table = read.delim(file="~/neuron_rna_seq/hypodermis_table.txt", header=FALSE, stringsAsFactors=TRUE)
> cds = newCountDataSetFromHTSeqCount(table, directory="~/neuron_rna_seq")
> cds = estimateSizeFactors( cds )
> sizeFactors( cds )
hypodermis hypodermis_unfiltered
0.3333333 3.0000000
> cds = estimateDispersions(cds, method="blind", sharingMode="fit-only")
Error in parametricDispersionFit(means, disps) :
Parametric dispersion fit failed. Try a local fit and/or a pooled estimation. (See '?estimateDispersions')
In addition: Warning message:
glm.fit: algorithm did not converge
#Because of this I use the local fit
> cds = estimateDispersions(cds, method="blind", sharingMode="fit-only", fitType="local")
> results = nbinomTest(cds, "hypodermis", "hypodermis_unfiltered")
#Error in question
Error in if (dispTable(cds)[condA] == "blind" || dispTable(cds)[condB] == :
missing value where TRUE/FALSE needed
I apologize if this is a basic question, I'm not an experienced user.
Thanks!
April
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