On Wed, May 6, 2009 at 12:40 PM, Ivan Gregoretti <[email protected]> wrote:
> Hello Bioc-sig-seq, > > Say you run your ChIP-seq and find binding positions like this > > chr1 3660781 3662707 > chr1 4481742 4482656 > chr1 4482813 4484003 > chr1 4561320 4562262 > chr1 4774887 4776304 > chr1 4797291 4798822 > chr1 4847807 4848846 > chr1 5008093 5009386 > chr1 5009514 5010046 > chr1 5010095 5010583 > ...[many more loci and chromosomes]... > > Then you want to compare it to published data like this > > chr1 3659579 3662079 > chr1 4773791 4776291 > chr1 4797473 4799973 > chr1 4847394 4849894 > chr1 5007460 5009960 > chr1 5072753 5075253 > chr1 6204242 6206742 > chr1 7078730 7081230 > chr1 9282452 9284952 > chr1 9683423 9685923 > ...[many more loci and chromosomes]... > > What method would you use to test whether these two lists are > significantly different? > This is a tough statistical question that probably needs to be a bit more specific, but as far as technical tools, in addition to genomeIntervals there is the IRanges package and its efficient "overlap" function. IRanges is well integrated with the rest of sequence analysis infrastructure in Bioconductor. > > Any pointer would be appreciated. > > Ivan > > Ivan Gregoretti, PhD > National Institute of Diabetes and Digestive and Kidney Diseases > National Institutes of Health > 5 Memorial Dr, Building 5, Room 205. > Bethesda, MD 20892. USA. > Phone: 1-301-496-1592 > Fax: 1-301-496-9878 > > _______________________________________________ > Bioc-sig-sequencing mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing > [[alternative HTML version deleted]] _______________________________________________ Bioc-sig-sequencing mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing
