DESeq's estimateDispersions does not work
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Entering edit mode
@janghj12000-9827
Last seen 8.8 years ago

Hello

I am trying to use deseq.

I think I follow all instruction, but it does not work.

 

The following is the error message

Error in glm.fit(x = numeric(0), y = numeric(0), weights = NULL, start = c(0.1,  :
  object 'fit' not found
Calls: estimateDispersions ... parametricDispersionFit -> glm -> eval -> eval -> glm.fit
In addition: Warning messages:
1: In glm.fit(x = numeric(0), y = numeric(0), weights = NULL, start = c(0.1,  :
  no observations informative at iteration 1
2: glm.fit: algorithm did not converge
Execution halted

 

The following is count table (tab delimetered)

gene    treated     treated     notTreated     notTreated
test1 0       0       1       2
test3  394     718     1162    1513
test3        0       0       0       0
test4        0       0       0       0
test5        0       0       0       0

 

The following is my r script

#!/usr/bin/env Rscript

library(DESeq)

#parameters
args = commandArgs(trailingOnly=TRUE)
inFname=args[1]
outDir=args[2]
type1=args[3]
type2=args[4]

countTable <- read.delim(inFname, header=TRUE)
rownames(countTable) <- countTable$gene
countTable <- countTable[,-1]

#treatment infomation
conds <- factor(c(type1, type1, type2, type2))
cds <- newCountDataSet(countTable, conds)

#nomalization
cds <- estimateSizeFactors( cds )

head(counts(cds))

#variance estimation
cds <- estimateDispersions( cds )
print("------------------------------")
cds
print("==============================")

#calling differential expression
res = nbinomTest(cds, type1, type2)

head(res)

pdfFname = paste0(outDir, "graph.pdf")
pdf(pdfFname)
plotMA(res)

dev.off()

 

 

Can you tell me what I have done wrong.

Thank you

error in glm.fit • 1.6k views
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Entering edit mode
@wolfgang-huber-3550
Last seen 3 months ago
EMBL European Molecular Biology Laborat…

Please switch to DESeq2. You can consult the workflow http://f1000research.com/articles/4-1070/v1 for lots of advice.

 

The only reason anyone should still be using DESeq is if they have a legacy workflow and too much inertia to update.

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