{"id":10042,"date":"2020-06-29T09:36:52","date_gmt":"2020-06-29T09:36:52","guid":{"rendered":"https:\/\/bgrssb.icgbio.ru\/2020\/2020\/06\/29\/peak-caller-comparison-through-quality-control-of-chip-seq-datasets\/"},"modified":"2020-06-29T09:36:52","modified_gmt":"2020-06-29T09:36:52","slug":"peak-caller-comparison-through-quality-control-of-chip-seq-datasets","status":"publish","type":"post","link":"https:\/\/bgrssb.icgbio.ru\/2020\/2020\/06\/29\/peak-caller-comparison-through-quality-control-of-chip-seq-datasets\/","title":{"rendered":"Peak caller comparison through quality control of ChIP-Seq datasets"},"content":{"rendered":"<p>Ruslan N. Sharipov<sup>1<\/sup>, Yury V. Kondrakhin<sup>2<\/sup>, Semyon K. Kolmykov<sup>3<\/sup>, Ivan S. Yevshin<sup>4<\/sup>, Anna S. Ryabova<sup>5<\/sup>, Fedor A. Kolpakov<sup>6<\/sup><br \/><sup>1<\/sup>BIOSOFT.RU, LLC; Novosibirsk State University Novosibirsk, Russia, shrus79@biosoft.ru<br \/><sup>2<\/sup>Institute of Computational Technologies SB RAS; BIOSOFT.RU, LLC, Novosibirsk, Russia, yvkondrat@mail.ru<br \/><sup>3<\/sup>FRC Institute of Cytology and Genetics SB RAS; Institute of Computational Technologies SB RAS, Novosibirsk, Russia, kolmykovsk@gmail.com<br \/><sup>4<\/sup>Institute of Computational Technologies SB RAS; BIOSOFT.RU, LLC Novosibirsk, Russia, ivan@biosoft.ru<br \/><sup>5<\/sup>Institute of Computational Technologies SB RAS; BIOSOFT.RU, LLC Novosibirsk, Russia, anna@biosoft.ru<br \/><sup>6<\/sup>Institute of Computational Technologies SB RAS; BIOSOFT.RU, LLC Novosibirsk, Russia, fedor@biosoft.ru<\/p>\n<p><strong>Chromatin immunoprecipitation followed by high throughput sequencing, i.e. ChIP-Seq, is a widely used experimental technology for the identification of functional protein-DNA interactions. Nowadays, such databases as GTRD, ChIP-Atlas and ReMap systematically collect and annotate a large number of ChIP-Seq datasets generated by distinct peak callers, including MACS2. The quality control of such datasets is currently indispensable, since the peak callers may produce different results for the same ChIP-seq experiment. We have performed a comparative analysis of intensively used peak callers with the help of two metrics that control false positive\/negative rates. We have found that MACS2 outperformed its competitors.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Ruslan N. Sharipov1, Yury V. Kondrakhin2, Semyon K. Kolmykov3, Ivan S. Yevshin4, Anna S. Ryabova5, Fedor A. Kolpakov61BIOSOFT.RU, LLC; Novosibirsk State University Novosibirsk, Russia, shrus79@biosoft.ru2Institute of Computational Technologies SB RAS; BIOSOFT.RU, LLC, Novosibirsk, Russia, yvkondrat@mail.ru3FRC Institute of Cytology and Genetics SB RAS; Institute of Computational Technologies SB RAS, Novosibirsk, Russia, kolmykovsk@gmail.com4Institute of Computational Technologies SB RAS; BIOSOFT.RU, LLC Novosibirsk, Russia, ivan@biosoft.ru5Institute of Computational Technologies SB RAS; BIOSOFT.RU, LLC Novosibirsk, Russia, anna@biosoft.ru6Institute of Computational Technologies SB RAS; BIOSOFT.RU, LLC Novosibirsk, Russia, fedor@biosoft.ru Chromatin immunoprecipitation followed by high throughput sequencing, i.e. ChIP-Seq, is a widely used experimental technology for the identification of functional protein-DNA interactions. Nowadays, such databases as GTRD, ChIP-Atlas and ReMap systematically collect and annotate a large number of ChIP-Seq datasets generated by distinct peak callers, including MACS2. The quality control of such datasets is currently indispensable, since the peak callers may produce different results for the same ChIP-seq experiment. We have performed a comparative analysis of intensively used peak callers with the help of two metrics that control false positive\/negative rates. We have found that MACS2 outperformed its competitors.<\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2171],"tags":[1294,1297,1296,1298,1295,1293],"_links":{"self":[{"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/posts\/10042"}],"collection":[{"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/comments?post=10042"}],"version-history":[{"count":0,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/posts\/10042\/revisions"}],"wp:attachment":[{"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/media?parent=10042"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/categories?post=10042"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/tags?post=10042"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}