{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T12:15:01Z","timestamp":1775736901864,"version":"3.50.1"},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2014,5,10]],"date-time":"2014-05-10T00:00:00Z","timestamp":1399680000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,9,1]]},"abstract":"<jats:p>Summary: We created a fast, robust and general C++ implementation of a single-nucleotide polymorphism (SNP) set enrichment algorithm to identify cell types, tissues and pathways affected by risk loci. It tests trait-associated genomic loci for enrichment of specificity to conditions (cell types, tissues and pathways). We use a non-parametric statistical approach to compute empirical P-values by comparison with null SNP sets. As a proof of concept, we present novel applications of our method to four sets of genome-wide significant SNPs associated with red blood cell count, multiple sclerosis, celiac disease and HDL cholesterol.<\/jats:p>\n               <jats:p>Availability and implementation: \u00a0http:\/\/broadinstitute.org\/mpg\/snpsea<\/jats:p>\n               <jats:p>Contact: \u00a0soumya@broadinstitute.org<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary Data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu326","type":"journal-article","created":{"date-parts":[[2014,5,11]],"date-time":"2014-05-11T00:36:58Z","timestamp":1399768618000},"page":"2496-2497","source":"Crossref","is-referenced-by-count":86,"title":["SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci"],"prefix":"10.1093","volume":"30","author":[{"given":"Kamil","family":"Slowikowski","sequence":"first","affiliation":[{"name":"1 \u00a01Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, 2Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, 3Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA and 4Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA"}]},{"given":"Xinli","family":"Hu","sequence":"additional","affiliation":[{"name":"1 \u00a01Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, 2Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, 3Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA and 4Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA"}]},{"given":"Soumya","family":"Raychaudhuri","sequence":"additional","affiliation":[{"name":"1 \u00a01Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, 2Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, 3Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA and 4Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA"}]}],"member":"286","published-online":{"date-parts":[[2014,5,10]]},"reference":[{"key":"2023012711525920000_btu326-B1","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/75556","article-title":"Gene Ontology: tool for the unification of biology","volume":"25","author":"Botstein","year":"2000","journal-title":"Nat. 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