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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