Limma package and minimal number of genes
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@bas-van-gestel-6599
Last seen 9.6 years ago
Dear all, Currently, I'm comparing the gene expression of three cell types to identify differentially expressed genes. For this purpose, the limma package seems ideal. However, for one of the analyses, I would like to focus only on the transcription factors of the cell types. This implies that I only consider about 990 genes. Is this enough to perform an analysis with limma, or does it require a larger number of genes at minimum to give reliable results? Kind regards, Bas van Gestel [[alternative HTML version deleted]]
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@bas-van-gestel-6508
Last seen 9.6 years ago
Dear all, Currently, I'm comparing the gene expression of three cell types to identify differentially expressed genes. For this purpose, the limma package seems ideal. However, for one of the analyses, I would like to focus only on the transcription factors of the cell types. This implies that I only consider about 990 genes. Is this enough to perform an analysis with limma, or does it require a larger number of genes at minimum to give reliable results? Kind regards, Bas van Gestel [[alternative HTML version deleted]]
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@ryan-c-thompson-5618
Last seen 7 months ago
Scripps Research, La Jolla, CA
Hello, I believe Gordon has stated in the past that limma can be used with as few as 4 genes. -Ryan On Tue Jun 10 01:34:08 2014, Bas van Gestel wrote: > Dear all, > > Currently, I'm comparing the gene expression of three cell types to > identify differentially expressed genes. For this purpose, the limma > package seems ideal. However, for one of the analyses, I would like to > focus only on the transcription factors of the cell types. This implies > that I only consider about 990 genes. Is this enough to perform an analysis > with limma, or does it require a larger number of genes at minimum to give > reliable results? > > Kind regards, > Bas van Gestel > > [[alternative HTML version deleted]] > > _______________________________________________ > 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
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Paul Geeleher ★ 1.3k
@paul-geeleher-2679
Last seen 9.6 years ago
Limma borrows information across all genes to better estimate variance for each gene, so your results should in theory be more accurate if you run the analysis for all genes on your arrays and export the p-values for the set of genes in which you are interested at the end of the analysis. Paul On Tue, Jun 10, 2014 at 3:34 AM, Bas van Gestel <shc.van.gestel at="" gmail.com=""> wrote: > Dear all, > > Currently, I'm comparing the gene expression of three cell types to > identify differentially expressed genes. For this purpose, the limma > package seems ideal. However, for one of the analyses, I would like to > focus only on the transcription factors of the cell types. This implies > that I only consider about 990 genes. Is this enough to perform an analysis > with limma, or does it require a larger number of genes at minimum to give > reliable results? > > Kind regards, > Bas van Gestel > > [[alternative HTML version deleted]] > > _______________________________________________ > 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 -- Dr. Paul Geeleher, PhD Section of Hematology-Oncology Department of Medicine The University of Chicago 900 E. 57th St., KCBD, Room 7144 Chicago, IL 60637 -- www.bioinformaticstutorials.com
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Ah, yes, re-reading the original question, this is the correct answer. Filtering genes by biological annotation (e.g. just TFs) should be done after running limma. On Tue Jun 10 19:47:59 2014, Paul Geeleher wrote: > Limma borrows information across all genes to better estimate variance > for each gene, so your results should in theory be more accurate if > you run the analysis for all genes on your arrays and export the > p-values for the set of genes in which you are interested at the end > of the analysis. > > Paul > > On Tue, Jun 10, 2014 at 3:34 AM, Bas van Gestel > <shc.van.gestel at="" gmail.com=""> wrote: >> Dear all, >> >> Currently, I'm comparing the gene expression of three cell types to >> identify differentially expressed genes. For this purpose, the limma >> package seems ideal. However, for one of the analyses, I would like to >> focus only on the transcription factors of the cell types. This implies >> that I only consider about 990 genes. Is this enough to perform an analysis >> with limma, or does it require a larger number of genes at minimum to give >> reliable results? >> >> Kind regards, >> Bas van Gestel >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> 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 > > >
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