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Question: Limma package and minimal number of genes
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gravatar for Bas van Gestel
3.4 years ago by
Bas van Gestel10 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]]
ADD COMMENTlink modified 3.4 years ago by Paul Geeleher1.3k • written 3.4 years ago by Bas van Gestel10
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gravatar for Bas van Gestel
3.4 years ago by
Bas van Gestel20 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]]
ADD COMMENTlink written 3.4 years ago by Bas van Gestel20
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gravatar for Ryan C. Thompson
3.4 years ago by
The Scripps Research Institute, La Jolla, CA
Ryan C. Thompson6.1k wrote:
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
ADD COMMENTlink written 3.4 years ago by Ryan C. Thompson6.1k
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gravatar for Paul Geeleher
3.4 years ago by
Paul Geeleher1.3k
Paul Geeleher1.3k 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 -- 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
ADD COMMENTlink written 3.4 years ago by Paul Geeleher1.3k
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 > > >
ADD REPLYlink written 3.4 years ago by Ryan C. Thompson6.1k
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