tag:blogger.com,1999:blog-8959227089815463704.post4050500156487201205..comments2023-10-02T17:00:45.520+08:00Comments on Kevin's GATTACA World: genomeCoverageBed to look at coverage of your WGSUnknownnoreply@blogger.comBlogger4125tag:blogger.com,1999:blog-8959227089815463704.post-83510134931269460032012-10-18T01:51:57.248+08:002012-10-18T01:51:57.248+08:00Thanks okKo for suggesting excellent tool. Thanks ...Thanks okKo for suggesting excellent tool. Thanks kevin for maintaing blog, it is really helpful for newbies.jacknoreply@blogger.comtag:blogger.com,1999:blog-8959227089815463704.post-53325998841603520002012-06-08T20:22:09.313+08:002012-06-08T20:22:09.313+08:00BAM QC tool from QualiMap (http://qualimap.org) pr...BAM QC tool from QualiMap (http://qualimap.org) provides a coverage plot. See example output here: http://qualimap.bioinfo.cipf.es/samples/ERR089819_result/qualimapReport.htmlKonstantin Okonechnikovhttps://www.blogger.com/profile/18330971587943165469noreply@blogger.comtag:blogger.com,1999:blog-8959227089815463704.post-28858072785632107302011-08-04T01:51:57.460+08:002011-08-04T01:51:57.460+08:00This is one of those cases where Bioconductor is e...This is one of those cases where Bioconductor is especially useful because you have access to all the genome metadata contained in BSGenomes:<br />http://jermdemo.blogspot.com/2010/12/chromosome-bias-in-r-my-notebook.htmlJermdemohttps://www.blogger.com/profile/01662705354227625640noreply@blogger.comtag:blogger.com,1999:blog-8959227089815463704.post-82943507013429083832011-07-04T14:11:20.452+08:002011-07-04T14:11:20.452+08:00You can also just do a samtools idxstats on the in...You can also just do a samtools idxstats on the indexed BAM file and the first two columns are the chromosome and size. <br /><br />I have an issue with genomeCoverageBed used this way, though: It will include all the heterochromatin (centromeres) in its calculation.<br /><br />Is it really fair to include that in a calculation of coverage if those sequences aren't even present in the reference genome you aligned to?<br /><br />I guess that kind of leads down the path of asking whether genome-wide coverage is a particularly meaningful statistic at all, and if it's not, what replacement statistic is.<br /><br />A simple solution is to use coverageBed instead, and utilize the "gaps" track from UCSC (Tables->All Tracks->Gap) for your particular genome. This track basically just has blocks where there is no genomic assembly in that version of the genome (and therefore, those positions inherently are not mappable since the reference isn't even known). Instead of using the whole genome, calculate coverage across everything that isn't in a gap. Of course, not everything outside the gaps is mappable, but a much greater percent of that region is and, at the very least, those bases are present in the reference genome.Anonymoushttps://www.blogger.com/profile/15925017686062610434noreply@blogger.com