{"id":380,"date":"2016-04-07T10:20:15","date_gmt":"2016-04-07T15:20:15","guid":{"rendered":"http:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/?p=380"},"modified":"2016-05-03T12:00:48","modified_gmt":"2016-05-03T17:00:48","slug":"analysis-of-computational-footprinting-methods-for-dnase-sequencing-experiments","status":"publish","type":"post","link":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/2016\/04\/07\/analysis-of-computational-footprinting-methods-for-dnase-sequencing-experiments\/","title":{"rendered":"Analysis of computational footprinting methods for DNase sequencing experiments"},"content":{"rendered":"<p>Our paper for the next journal club meeting on 4\/18\/2016 is <a href=\"http:\/\/www.nature.com\/nmeth\/journal\/v13\/n4\/full\/nmeth.3772.html\">Analysis of computational footprinting methods for DNase sequencing experiments<\/a> by Gusmao et al. (Nature Methods, 2016). The abstract is as follows.<\/p>\n<blockquote><p>DNase-seq allows nucleotide-level identification of transcription factor binding sites on the basis of a computational search of footprint-like DNase I cleavage patterns on the DNA. Frequently in high-throughput methods, experimental artifacts such as DNase I cleavage bias affect the computational analysis of DNase-seq experiments. Here we performed a comprehensive and systematic study on the performance of computational footprinting methods. We evaluated ten footprinting methods in a panel of DNase-seq experiments for their ability to recover cell-specific transcription factor binding sites. We show that three methods\u2014HINT, DNase2TF and PIQ\u2014consistently outperformed the other evaluated methods and that correcting the DNase-seq signal for experimental artifacts significantly improved the accuracy of computational footprints. We also propose a score that can be used to detect footprints arising from transcription factors with potentially short residence times.<\/p><\/blockquote>\n<p>Feel free to begin the discussion in the Comments section below. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Our paper for the next journal club meeting on 4\/18\/2016 is Analysis of computational footprinting methods for DNase sequencing experiments by Gusmao et al. (Nature Methods, 2016). The abstract is as follows. DNase-seq allows nucleotide-level identification of transcription factor binding sites on the basis of a computational search of footprint-like DNase I cleavage patterns on [&hellip;]<\/p>\n","protected":false},"author":124,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[102,98,1],"tags":[],"_links":{"self":[{"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/posts\/380"}],"collection":[{"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/users\/124"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/comments?post=380"}],"version-history":[{"count":2,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/posts\/380\/revisions"}],"predecessor-version":[{"id":386,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/posts\/380\/revisions\/386"}],"wp:attachment":[{"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/media?parent=380"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/categories?post=380"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/sysbiojournalclub\/wp-json\/wp\/v2\/tags?post=380"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}