Dear all,
I am analyzing a RNA-seq experiment with DEXSeq. There are 73 samples (from 23 different conditions).
When trying to estimate the dispersions for the whole exonCountSet (all conditions together), I am running out of memory and the job terminates. I increased the maximum allowed memory to 128G for this job, but it seems to be still too little.
Is this function supposed to use as much memory?
Does anyone have some experience to share about the analysis of large datasets with DEXSeq?
I am analyzing a RNA-seq experiment with DEXSeq. There are 73 samples (from 23 different conditions).
When trying to estimate the dispersions for the whole exonCountSet (all conditions together), I am running out of memory and the job terminates. I increased the maximum allowed memory to 128G for this job, but it seems to be still too little.
Is this function supposed to use as much memory?
Does anyone have some experience to share about the analysis of large datasets with DEXSeq?
Code:
## The design and sample annotation is in data frame called "samples" > library("DEXSeq") > library(parallel) > allExons <- read.HTSeqCounts(countfiles = file.path("prepared_counts", rownames(samples), "counts_DEXSeq.txt"), design = samples, flattenedfile = annotationfile) > sampleNames(allExons) <- rownames(samples) > allExons <- estimateSizeFactors(allExons) > allExons <- estimateDispersions(allExons, nCores=8, minCount = 100, file = "DEXSeq_output.out") > sessionInfo() R version 2.15.0 (2012-03-30) Platform: x86_64-redhat-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=C LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] parallel stats graphics grDevices utils datasets methods [8] base other attached packages: [1] DEXSeq_1.4.0 Biobase_2.16.0 BiocGenerics_0.4.0 loaded via a namespace (and not attached): [1] biomaRt_2.12.0 hwriter_1.3 plyr_1.7.1 RCurl_1.91-1 statmod_1.4.16 [6] stringr_0.6 XML_3.9-4
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