{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T03:03:00Z","timestamp":1761102180443},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,1,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents\u2019 potency and experimental noise must be accounted for appropriately control for false positives. Indeed, rigorous statistical analysis of high-throughput FG screening data remains challenging, particularly when integrative analyses are used to combine multiple sh\/sgRNAs targeting the same gene in the library.<\/jats:p><jats:p>Method: We use large RNAi and CRISPR repositories that are publicly available to evaluate a novel meta-analysis approach for FG screens via Bayesian hierarchical modeling, Screening Bayesian Evaluation and Analysis Method (ScreenBEAM).<\/jats:p><jats:p>Results: Results from our analysis show that the proposed strategy, which seamlessly combines all available data, robustly outperforms classical algorithms developed for microarray data sets as well as recent approaches designed for next generation sequencing technologies. Remarkably, the ScreenBEAM algorithm works well even when the quality of FG screens is relatively low, which accounts for about 80\u201395% of the public datasets.<\/jats:p><jats:p>Availability and implementation: R package and source code are available at: https:\/\/github.com\/jyyu\/ScreenBEAM.<\/jats:p><jats:p>Contact: ac2248@columbia.edu, jose.silva@mssm.edu, yujiyang@gmail.com<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv556","type":"journal-article","created":{"date-parts":[[2015,9,29]],"date-time":"2015-09-29T01:59:04Z","timestamp":1443491944000},"page":"260-267","source":"Crossref","is-referenced-by-count":38,"title":["ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling"],"prefix":"10.1093","volume":"32","author":[{"given":"Jiyang","family":"Yu","sequence":"first","affiliation":[{"name":"1 Department of Biomedical Informatics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA and"}]},{"given":"Jose","family":"Silva","sequence":"additional","affiliation":[{"name":"2 Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA"}]},{"given":"Andrea","family":"Califano","sequence":"additional","affiliation":[{"name":"1 Department of Biomedical Informatics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA and"}]}],"member":"286","published-online":{"date-parts":[[2015,9,28]]},"reference":[{"key":"2023020110281738500_btv556-B1","doi-asserted-by":"crossref","first-page":"5818","DOI":"10.1158\/0008-5472.CAN-11-0778","article-title":"STK33 Kinase activity is nonessential in KRAS-dependent cancer cells","volume":"71","author":"Babij","year":"2011","journal-title":"Cancer Res."},{"key":"2023020110281738500_btv556-B2","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1038\/483531a","article-title":"Drug development: raise standards for preclinical cancer research","volume":"483","author":"Begley","year":"2012","journal-title":"Nature"},{"key":"2023020110281738500_btv556-B3","doi-asserted-by":"crossref","first-page":"e22859","DOI":"10.1371\/journal.pone.0022859","article-title":"Identification of human housekeeping genes and tissue-selective genes by microarray meta-analysis","volume":"6","author":"Chang","year":"2011","journal-title":"PLoS One"},{"key":"2023020110281738500_btv556-B4","doi-asserted-by":"crossref","first-page":"12372","DOI":"10.1073\/pnas.1109363108","article-title":"Systematic investigation of genetic vulnerabilities across cancer cell lines reveals lineage-specific dependencies in ovarian cancer","volume":"108","author":"Cheung","year":"2011","journal-title":"Proc. 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