DESeqDataSetFromHTSeqCount function taking long time and utilizing more RAM
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2.2 years ago

I am using DESeq2 for differential gene expression. I have done alignment using STAR aligner and GRCh38 reference genome. I have generated count files using HTSeq. I have 3 controls and 4 cases and the size of each count file varies from 8 GB to 11 GB which makes to total 73 GB of data (7 Count files).

ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, directory = directory, design = ~ condition) directory where I kept the count files. This command is taking more than 12 hours and consumed memory of 46 GB. I have a maximum memory limit of 64 GB in my System.

Could anyone help how to solve this problem? ![Screenshot is given here...][1] [1]: https://ibb.co/3s48HRw

RNA-Seq DESeq2 R Tool • 853 views
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size of each count file varies from 8 GB to 11 GB

That is not likely to be correct. I assume these are original BAM alignment files. Even with 10 samples a count matrix file for featureCounts for mouse samples is < 30 MB.

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Something is not right here. Please share all relevant command lines. Is this normal RNA-seq?

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Yes. This is a normal RNA-seq.

directory="~/Desktop/deseq2/"
setwd(directory)
sampleNames<- c("AN_d83", "AN_d85","AN_d86", "Tum_t83","Tum_t84","Tum_t85","Tum_t86")
sampleTable <- data.frame(sampleName = sampleNames, fileName = sampleFiles, condition = sampleCondition)
library("DESeq2")
ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, directory = directory, design = ~ condition)

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As genomax says these files are way to big for count matrices. The loading process should take a couple of seconds actually and should be possible on any standard laptop. Check that file paths are correct and really direct to the count matrices, not to the bam files.

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Thanks, Problem is solved.

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Please add the solution to the answer field if others encounter the same problem.

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