ChIP-BIT: Bayesian inference of target genes using a novel joint probabilistic model of ChIP-seq profiles

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dc.contributorVirginia Techen
dc.contributor.authorChen, Xien
dc.contributor.authorJung, Jin-Gyoungen
dc.contributor.authorShajahan-Haq, Ayesha N.en
dc.contributor.authorClarke, Roberten
dc.contributor.authorShih, Ie-Mingen
dc.contributor.authorWang, Yueen
dc.contributor.authorMagnani, Lucaen
dc.contributor.authorWang, Tian-Lien
dc.contributor.authorXuan, Jianhuaen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2017-03-13T17:13:41Zen
dc.date.available2017-03-13T17:13:41Zen
dc.date.issued2015-12-23en
dc.description.abstractChromatin immunoprecipitation with massively parallel DNA sequencing (ChIP-seq) has greatly improved the reliability with which transcription factor binding sites (TFBSs) can be identified from genome-wide profiling studies. Many computational tools are developed to detect binding events or peaks, however the robust detection of weak binding events remains a challenge for current peak calling tools. We have developed a novel Bayesian approach (ChIP-BIT) to reliably detect TFBSs and their target genes by jointly modeling binding signal intensities and binding locations of TFBSs. Specifically, a Gaussian mixture model is used to capture both binding and background signals in sample data. As a unique feature of ChIP-BIT, background signals are modeled by a local Gaussian distribution that is accurately estimated from the input data. Extensive simulation studies showed a significantly improved performance of ChIP-BIT in target gene prediction, particularly for detecting weak binding signals at gene promoter regions. We applied ChIP-BIT to find target genes from NOTCH3 and PBX1 ChIP-seq data acquired from MCF-7 breast cancer cells. TF knockdown experiments have initially validated about 30% of co-regulated target genes identified by ChIP-BIT as being differentially expressed in MCF-7 cells. Functional analysis on these genes further revealed the existence of crosstalk between Notch and Wnt signaling pathways.en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1093/nar/gkv1491en
dc.identifier.issue7en
dc.identifier.urihttp://hdl.handle.net/10919/76636en
dc.identifier.volume44en
dc.language.isoenen
dc.publisherOxforden
dc.rightsCreative Commons Attribution Non-Commercial 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en
dc.titleChIP-BIT: Bayesian inference of target genes using a novel joint probabilistic model of ChIP-seq profilesen
dc.title.serialNucleic Acids Researchen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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