{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T12:15:20Z","timestamp":1768738520814,"version":"3.49.0"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2018,4,6]],"date-time":"2018-04-06T00:00:00Z","timestamp":1522972800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["K01LM012426"],"award-info":[{"award-number":["K01LM012426"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Gene set testing, or pathway analysis, has become a critical tool for the analysis of high-dimensional genomic data. Although the function and activity of many genes and higher-level processes is tissue-specific, gene set testing is typically performed in a tissue agnostic fashion, which impacts statistical power and the interpretation and replication of results.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>To address this challenge, we have developed a bioinformatics approach to compute tissue-specific weights for individual gene sets using information on tissue-specific gene activity from the Human Protein Atlas (HPA). We used this approach to create a public repository of tissue-specific gene set weights for 37 different human tissue types from the HPA and all collections in the Molecular Signatures Database. To demonstrate the validity and utility of these weights, we explored three different applications: the functional characterization of human tissues, multi-tissue analysis for systemic diseases and tissue-specific gene set testing.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>All data used in the reported analyses is publicly available. An R implementation of the method and tissue-specific weights for MSigDB gene set collections can be downloaded at http:\/\/www.dartmouth.edu\/\u223chrfrost\/TissueSpecificGeneSets.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty217","type":"journal-article","created":{"date-parts":[[2018,4,4]],"date-time":"2018-04-04T19:12:36Z","timestamp":1522869156000},"page":"2957-2964","source":"Crossref","is-referenced-by-count":11,"title":["Computation and application of tissue-specific gene set weights"],"prefix":"10.1093","volume":"34","author":[{"given":"H Robert","family":"Frost","sequence":"first","affiliation":[{"name":"Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH, USA"}]}],"member":"286","published-online":{"date-parts":[[2018,4,6]]},"reference":[{"key":"2023061313365990400_bty217-B1","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1038\/nrg1749","article-title":"Microarray data analysis: from disarray to consolidation and consensus","volume":"7","author":"Allison","year":"2006","journal-title":"Nat. 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