I am trying to find a way to perform pairwise correlations against one gene in a matrix rather than computing every pairwise correlation. I am interested in how 1 transcription factor correlates to every gene in a matrix of 55 experiments (columns) by 23,000 genes (rows), performing the correlation by rows. Trying to perform every pairwise correlation in this fashion is too memory intensive for any computer I am currently using so I am wondering if anyone had a method for doing pairwise correlations to a single gene or if there is a preexisting package in R that might address this. Damion Nero Plant Molecular Biology Lab Department of Biology New York University
Correlation to a Single Gene
3 messages · Damion Colin Nero, Charles C. Berry, Robert Gentleman
On Wed, 17 Jan 2007, Damion Colin Nero wrote:
I am trying to find a way to perform pairwise correlations against one gene in a matrix rather than computing every pairwise correlation. I am interested in how 1 transcription factor correlates to every gene in a matrix of 55 experiments (columns) by 23,000 genes (rows), performing the correlation by rows. Trying to perform every pairwise correlation in this fashion is too memory intensive for any computer I am currently using so I am wondering if anyone had a method for doing pairwise correlations to a single gene or if there is a preexisting package in R that might address this.
You measure the transcription factor once in each of 55 experiments and you measure gene *expression* (or some other quantity) on each of 23000 genes? cor.vec <- cor (transfac, t( gene.mat ) ) will do. Questions like this might best be posted to the bioconductor mail list.
Damion Nero Plant Molecular Biology Lab Department of Biology New York University
______________________________________________ R-help at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Charles C. Berry (858) 534-2098
Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu UC San Diego
http://biostat.ucsd.edu/~cberry/ La Jolla, San Diego 92093-0901
In the package genefilter, from www.bioconductor.org there is a function to do this (genefinder, if I recall correctly) best wishes Robert
Charles C. Berry wrote:
On Wed, 17 Jan 2007, Damion Colin Nero wrote:
I am trying to find a way to perform pairwise correlations against one gene in a matrix rather than computing every pairwise correlation. I am interested in how 1 transcription factor correlates to every gene in a matrix of 55 experiments (columns) by 23,000 genes (rows), performing the correlation by rows. Trying to perform every pairwise correlation in this fashion is too memory intensive for any computer I am currently using so I am wondering if anyone had a method for doing pairwise correlations to a single gene or if there is a preexisting package in R that might address this.
You measure the transcription factor once in each of 55 experiments and you measure gene *expression* (or some other quantity) on each of 23000 genes? cor.vec <- cor (transfac, t( gene.mat ) ) will do. Questions like this might best be posted to the bioconductor mail list.
Damion Nero Plant Molecular Biology Lab Department of Biology New York University
______________________________________________ R-help at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Charles C. Berry (858) 534-2098
Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu UC San Diego
http://biostat.ucsd.edu/~cberry/ La Jolla, San Diego 92093-0901
______________________________________________ R-help at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Robert Gentleman, PhD Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M2-B876 PO Box 19024 Seattle, Washington 98109-1024 206-667-7700 rgentlem at fhcrc.org