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Imène SENINET
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20
@imene-seninet-6652
Last seen 10.3 years ago
Hello,
Thank you for having invovled me in this mailing list :)
I am trying to measure gene expression differences using RNAseq data.
I
did several runs using the package R/DESeq. For my testing data I used
a
*.cvs file, i.e. a table of raw counts containing more than 10800000
reads with 2 conditions (no replicate)
I get the following error message after calling the function "cds
<-estimateDispersions(cds, method='blind',sharingMode='fit-only',
fitType='local')":
----------------------------------------------------------------------
----------------------------------------------------------------
/Error in lfproc(x, y, weights = weights, cens = cens, base = base,
geth
= geth, :
newsplit: out of vertex space
In addition: There were 50 or more warnings (use warnings() to see the
first 50) /
----------------------------------------------------------------------
-----------------------------------------------
I've read that this error is related to maxk parameter value in
locfit,
so I increased it from 300 to 11000000. But the provided solutions did
not work.
Would you please help me to find out what wrong with my test?
Thank you very much and kind regards,
Im?ne
---
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I have similar error messages with a recently installed DESeq2, that I run from python via r2py:
To make this even more complicated, this is run from snakemake, with which I regularly experience memory-related problems when I run too many processes in parallel. The "out of vertex space" message let me suspect that my problem was something similar, but the error persists even when running only one process. I will have to run the analysis "manually" from R to further reduce the potential sources of problems.
I confirm that the problem occurs when running the analysis manually:
Content of
test_DESeq2.R:library(DESeq2) counts_table = "results/bowtie2/mapped_C_elegans/annotation/all_18-26_on_C_elegans/simrep_siu_counts.txt" counts_data <- read.table(counts_table, header=T, row.names="gene") libs <- c(rep(c(rep("WT", times=3), rep("prg1", times=3)), times=2)) treats <- rep(c("RT", "HS30", "HS30RT120"), times=4) reps <- c(rep("1", times=6), rep("2", times=6)) col_data <- data.frame(lib=libs, treat=treats, rep=reps, lib_treat=paste(libs, treats, sep="_"), row.names=colnames(counts_data)) dds <- DESeqDataSetFromMatrix(countData=counts_data, colData=col_data, design=~ lib_treat) dds <- DESeq(dds, betaPrior=TRUE)Running it:
$ Rscript test_DESeq2.R
Loading required package: S4Vectors
Loading required package: methods
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: ‘BiocGenerics’
The following objects are masked from ‘package:parallel’:
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from ‘package:stats’:
IQR, mad, sd, var, xtabs
The following objects are masked from ‘package:base’:
anyDuplicated, append, as.data.frame, cbind, colMeans, colnames,
colSums, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
grepl, intersect, is.unsorted, lapply, lengths, Map, mapply, match,
mget, order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
rbind, Reduce, rowMeans, rownames, rowSums, sapply, setdiff, sort,
table, tapply, union, unique, unsplit, which, which.max, which.min
Attaching package: ‘S4Vectors’
The following object is masked from ‘package:base’:
expand.grid
Loading required package: IRanges
Loading required package: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: DelayedArray
Loading required package: matrixStats
Attaching package: ‘matrixStats’
The following objects are masked from ‘package:Biobase’:
anyMissing, rowMedians
Attaching package: ‘DelayedArray’
The following objects are masked from ‘package:matrixStats’:
colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges
The following object is masked from ‘package:base’:
apply
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
-- note: fitType='parametric', but the dispersion trend was not well captured by the
function: y = a/x + b, and a local regression fit was automatically substituted.
specify fitType='local' or 'mean' to avoid this message next time.
Error in lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth, :
newsplit: out of vertex space
Calls: DESeq ... estimateDispersionsFit -> localDispersionFit -> locfit -> lfproc -> .C
In addition: There were 12 warnings (use warnings() to see them)
Execution halted
I uploaded the contents of the
simrep_siu_counts.txtfile here: http://paste.ubuntu.com/24955101/