TMM Normalization without replicate
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Guest User ★ 13k
@guest-user-4897
Last seen 10.3 years ago
Hi, I am a graduate student at POSTECH and I ran into some troubles while running edgeR program. Currently I have six Chip-Seq samples, all of different condition. There are no biological replicate and no control sample. So when I try to run edgeR, it does not run for there is no biological replicate used for statistical testing. I wonder if there is a way to export TMM normalized count from edgeR package without compliting the program. I know the program should run up till calcNormFactor and give normfactor but without biological replicate, it cannot calculate dispersion and the whole program fails to run. Is there a way to export just the TMM normalized data without doing statistical testing? If so, what are the codes that allow such methods? I tried cpm function but cpm may use raw or normalized data not gives a normalized data from raw data. Thanks in advance, -- output of sessionInfo(): -- Sent via the guest posting facility at bioconductor.org.
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Mark Robinson ▴ 880
@mark-robinson-4908
Last seen 6.1 years ago
Hi Jieon, Some comments below. > Hi, I am a graduate student at POSTECH and I ran into some troubles while running edgeR program. > Currently I have six Chip-Seq samples, all of different condition. There are no biological replicate and no control sample. > So when I try to run edgeR, it does not run for there is no biological replicate used for statistical testing. Have you read the Section "What to do if you have no replicates" in the User's Guide: http://www.bioconductor.org/packages/release/bioc/vignettes/edgeR/inst /doc/edgeRUsersGuide.pdf > I wonder if there is a way to export TMM normalized count from edgeR package without compliting the program. > I know the program should run up till calcNormFactor and give normfactor but without biological replicate, it cannot calculate dispersion and the whole program fails to run. It does this for a reason. See comment above. > Is there a way to export just the TMM normalized data without doing statistical testing? > If so, what are the codes that allow such methods? > > I tried cpm function but cpm may use raw or normalized data not gives a normalized data from raw data. I'm not sure what you mean by this. What did you try? Something like this could work: d <- DGEList(<somecounts>) d <- calcNormFactors(d) cps <- cpm(d, normalized.lib.sizes=TRUE) write.table(cps, file="myCPMs.txt", sep="\t") Otherwise, I suggest you post a code example of what you have done. I also encourage you to read the posting guide: http://www.bioconductor.org/help/mailing-list/posting-guide/ Hope that helps. Best regards, Mark > > Thanks in advance, > > > -- output of sessionInfo(): > > > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor ---------- Prof. Dr. Mark Robinson Bioinformatics, Institute of Molecular Life Sciences University of Zurich http://tiny.cc/mrobin
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