Limma/oligo always crashing
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@hakimelakhrass-9661
Last seen 7.0 years ago

Hello All,

 

I am really having a lot of problems analysis hugene 2.0 st microarrays. 

My experimental setup is a control with 8 biological replicates then 3 timepoints with 9 replicates. The time points are months apart so it isn't really considered time series. 

 

R just keeps crashing when I try do anything above genelevel analysis. Prob level crashed. I am pretty lost. I want to get DE genes using all time points. I never worked with this type of data before. Can anyone help, give me a work flow. Teach me how to keep R from crashing.

 

Thank you

limma microarray pd.hugene.2.0.st hugene20 oligo • 2.3k views
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R has almost never crashed for me.

You will need to provide more information for us to help you. Please fire up R and load the packages you are using for your analysis, then update your post with

  1. The copy/pasted output from sessionInfo() 
  2. A copy of the code you are running, and point out where R is "crashing"

When you say crash? Is it, like, exploding or just throwing an error?

 

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Well I work in R study and it explodes and shuts down rStudio so I can't get sessioninfo(). 

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Well, I didn't ask you to run any of your analysis code. I just want you to load the relevant packages you are using (eg. oligo, and limma) then output the result from sessionInfo()

For the second ask: just copy/paste your code here, you don't have to run it.

Third: is the code always crashing at the same place? If so, please point out which command (in the R code that you will paste into your updated answer) is causing the crash.

Last: you might try just running your code from R fired up from the terminal (not through RStudio) to see if that makes a difference.

 

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@hakimelakhrass-9661
Last seen 7.0 years ago

okay so this is the first thing you asked for:

function (package = NULL) 
{
    z <- list()
    z$R.version <- R.Version()
    z$platform <- z$R.version$platform
    if (nzchar(.Platform$r_arch)) 
        z$platform <- paste(z$platform, .Platform$r_arch, sep = "/")
    z$platform <- paste0(z$platform, " (", 8 * .Machine$sizeof.pointer, 
        "-bit)")
    z$locale <- Sys.getlocale()
    if (is.null(package)) {
        package <- grep("^package:", search(), value = TRUE)
        keep <- sapply(package, function(x) x == "package:base" || 
            !is.null(attr(as.environment(x), "path")))
        package <- sub("^package:", "", package[keep])
    }
    pkgDesc <- lapply(package, packageDescription, encoding = NA)
    if (length(package) == 0) 
        stop("no valid packages were specified")
    basePkgs <- sapply(pkgDesc, function(x) !is.null(x$Priority) && 
        x$Priority == "base")
    z$basePkgs <- package[basePkgs]
    if (any(!basePkgs)) {
        z$otherPkgs <- pkgDesc[!basePkgs]
        names(z$otherPkgs) <- package[!basePkgs]
    }
    loadedOnly <- loadedNamespaces()
    loadedOnly <- loadedOnly[!(loadedOnly %in% package)]
    if (length(loadedOnly)) {
        names(loadedOnly) <- loadedOnly
        pkgDesc <- c(pkgDesc, lapply(loadedOnly, packageDescription))
        z$loadedOnly <- pkgDesc[loadedOnly]
    }
    class(z) <- "sessionInfo"
    z
}
<bytecode: 0xb60e1f8>
<environment: namespace:utils>

 

Second my code (I don't even know if this is the right directions for DE) :

source("http://bioconductor.org/biocLite.R")
biocLite("oligo")
biocLite("limma")
biocLite("pd.hugene.2.1.st")
library(genefilter)
library(limma)
library(oligo)
library(pd.hugene.2.0.st)

#directory for the data
mydir <- "/data/leuven/314/vsc31409/Bioinformatics_Thesis_Concordia_Microarry_Data/Control"

#setting seed for reproducibility
set.seed(1)
#listing the files from directory using special CEL file read function
celList <- list.celfiles(mydir, full.names=TRUE)
#reading data from cellist and setting annotation package to approiate one for this microarray
rawData <- read.celfiles(celList, pkgname='pd.hugene.2.0.st')
#normalizing the data using RMA algorithm
normData <- rma(rawData)
#checking boxplot of raw data
par(mar=c(10,4.5,2,1))
boxplot(rawData,las=3)
#checking boxplot of normalized data
boxplot(normData,las=3)

#the annotation package
biocLite("hugene20sttranscriptcluster.db")
library(hugene20sttranscriptcluster.db)

# Strategy is to create data frame objects and merge them together - put expression info into a data frame
my_frame <- data.frame(exprs(normData))

# Put annotation information in a data frame.  To get specific fields, use packageNameSYMBOL, where the caps part names the type of data you're after
hugene20sttranscriptcluster()
Annot <- data.frame(ACCNUM=sapply(contents(hugene20sttranscriptclusterACCNUM), paste, collapse=", "),
                    SYMBOL=sapply(contents(hugene20sttranscriptclusterSYMBOL), paste, collapse=", "), 
                    DESC=sapply(contents(hugene20sttranscriptclusterGENENAME), paste, collapse=", "))
#retreaving feature data

featureData(normData) <- getNetAffx(normData, "transcript")

#addomg phenotypic data

phn = normData@phenoData

phn@data[1:14,2]= "treated" 

phn@data[15:27,2]="control"

colnames(phn@data)[2]="source"

phn@data

# Merge data frames together (like a database table join) also removing NAs
all <- merge(Annot, my_frame, by.x=0, by.y=0, all=T)

merge <- subset(all, SYMBOL!="NA")

# Write out to a file:
write.table(merge,file="thesis.ann.txt",sep="\t")

#plm

Pset = fitProbeLevelModel(rawData) <-----This is where it crashes.

 

I will try running in regular R. Thank so much for the help!

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You should run sessionInfo(), not sessionInfo. The latter just returns the function itself.

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Almost ;-) I wanted the output when you execute the sessionInfo function, not the contents of the function itself.

Please copy and paste the following code into R, then provide us with the output that is returned when the last line completes (ie. after the call to sessionInfo() [note that I am calling the function because of the double parens, you just pasted the output of calling sessionInfo w/o parens, which is simply the function definition)

library(limma)
library(oligo)
sessionInfo()

This is the output when I run this in a fresh session for me. What you copy/paste should look roughly similar, but version numbers and such may differ.

R version 3.2.3 (2015-12-10)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.10.5 (Yosemite)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets
[8] methods   base

other attached packages:
 [1] oligo_1.34.2        Biostrings_2.38.3   XVector_0.10.0
 [4] IRanges_2.4.6       S4Vectors_0.8.11    Biobase_2.30.0
 [7] oligoClasses_1.32.0 BiocGenerics_0.16.1 limma_3.26.7
[10] devtools_1.10.0

loaded via a namespace (and not attached):
 [1] affxparser_1.42.0          splines_3.2.3
 [3] GenomicRanges_1.22.4       zlibbioc_1.16.0
 [5] bit_1.1-12                 foreach_1.4.3
 [7] GenomeInfoDb_1.6.3         tools_3.2.3
 [9] SummarizedExperiment_1.0.2 ff_2.2-13
[11] DBI_0.3.1                  iterators_1.0.8
[13] digest_0.6.9               preprocessCore_1.32.0
[15] crayon_1.3.1               affyio_1.40.0
[17] codetools_0.2-14           memoise_1.0.0
[19] RSQLite_1.0.0              BiocInstaller_1.20.1

 

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Here it is. Thank you for being patient. I never worked with this type of data before.

 

R version 3.0.2 (2013-09-25)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
[1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               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    LC_PAPER=en_US.UTF-8       LC_NAME=C                
[9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] pd.hugene.2.0.st_3.8.0 RSQLite_1.0.0          DBI_0.3.1              oligo_1.26.6         
[5] Biostrings_2.30.1      XVector_0.2.0          IRanges_1.20.7         Biobase_2.22.0       
[9] oligoClasses_1.24.0    BiocGenerics_0.8.0     limma_3.18.13          genefilter_1.44.0    
[13] BiocInstaller_1.12.1  

loaded via a namespace (and not attached):
[1] affxparser_1.34.2     affyio_1.30.0         Annotate_1.40.1       AnnotationDbi_1.24.0  bit_1.1-12          

​
[6] codetools_0.2-8       ff_2.2-13             foreach_1.4.3         GenomicRanges_1.14.4  iterators_1.0.8     
[11] preprocessCore_1.24.0 splines_3.0.2         stats4_3.0.2          survival_2.37-4       tools_3.0.2         
[16] XML_3.98-1.3          xtable_1.8-0          zlibbioc_1.8.0       
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Can you please try running your code without R Studio and sending (copy and paste the full session, including the error) to us?  Thank you very much, benilton  -------- Original message -------- From: "hakimelakhrass [bioc]" <noreply@bioconductor.org> Date: 04/02/2016 18:34 (GMT-03:00) To: benilton@unicamp.br Subject: [bioc] C: Limma/oligo always crashing Activity on a post you are following on support.bioconductor.org User hakimelakhrass wrote Comment: Limma/oligo always crashing: Here it is. Thank you for being patient. I never worked with this type of data before.   R version 3.0.2 (2013-09-25) Platform: x86_64-unknown-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C 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 LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] parallel stats graphics grDevices utils datasets methods base other attached packages: [1] pd.hugene.2.0.st_3.8.0 RSQLite_1.0.0 DBI_0.3.1 oligo_1.26.6 [5] Biostrings_2.30.1 XVector_0.2.0 IRanges_1.20.7 Biobase_2.22.0 [9] oligoClasses_1.24.0 BiocGenerics_0.8.0 limma_3.18.13 genefilter_1.44.0 [13] BiocInstaller_1.12.1 loaded via a namespace (and not attached): [1] affxparser_1.34.2 affyio_1.30.0 Annotate_1.40.1 AnnotationDbi_1.24.0 bit_1.1-12 ​ [6] codetools_0.2-8 ff_2.2-13 foreach_1.4.3 GenomicRanges_1.14.4 iterators_1.0.8 [11] preprocessCore_1.24.0 splines_3.0.2 stats4_3.0.2 survival_2.37-4 tools_3.0.2 [16] XML_3.98-1.3 xtable_1.8-0 zlibbioc_1.8.0 Post tags: limma, microarray, pd.hugene.2.0.st, hugene20, oligo You may reply via email or visit C: Limma/oligo always crashing
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My 2 cents: update to the latest version of R/BioC, and see whether your problem still persists. Your R-version is ~2.5 yrs old... Current is R3.2.3...

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Wow okay, so this worked. Thanks  a lot! Another question is if I am on the right direction for analysis DE genes. It is a little confusing to find the right way with there new arrays. Also the old quantitative QC functions don't work. The only ones I find are the visual ones but it would be nice to get some numbers. Any solutions?

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