{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:56Z","timestamp":1772138096336,"version":"3.50.1"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"22","license":[{"start":{"date-parts":[[2019,6,7]],"date-time":"2019-06-07T00:00:00Z","timestamp":1559865600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R03DE025665"],"award-info":[{"award-number":["R03DE025665"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Multi-trait analyses using public summary statistics from genome-wide association studies (GWASs) are becoming increasingly popular. A constraint of multi-trait methods is that they require complete summary data for all traits. Although methods for the imputation of summary statistics exist, they lack precision for genetic variants with small effect size. This is benign for univariate analyses where only variants with large effect size are selected a posteriori. However, it can lead to strong p-value inflation in multi-trait testing. Here we present a new approach that improve the existing imputation methods and reach a precision suitable for multi-trait analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We fine-tuned parameters to obtain a very high accuracy imputation from summary statistics. We demonstrate this accuracy for variants of all effect sizes on real data of 28 GWAS. We implemented the resulting methodology in a python package specially designed to efficiently impute multiple GWAS in parallel.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The python package is available at: https:\/\/gitlab.pasteur.fr\/statistical-genetics\/raiss, its accompanying documentation is accessible here http:\/\/statistical-genetics.pages.pasteur.fr\/raiss\/.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz466","type":"journal-article","created":{"date-parts":[[2019,6,4]],"date-time":"2019-06-04T07:40:34Z","timestamp":1559634034000},"page":"4837-4839","source":"Crossref","is-referenced-by-count":20,"title":["RAISS: robust and accurate imputation from summary statistics"],"prefix":"10.1093","volume":"35","author":[{"given":"Hanna","family":"Julienne","sequence":"first","affiliation":[{"name":"Groupe de G\u00e9n\u00e9tique Statistique, D\u00e9partement de G\u00e9nomes and G\u00e9n\u00e9tique, C3BI, Institut Pasteur , Paris, France"}]},{"given":"Huwenbo","family":"Shi","sequence":"additional","affiliation":[{"name":"Departments of Pathology and Lab Medicine, University of California , Los Angeles, Los Angeles, CA 90095, USA"}]},{"given":"Bogdan","family":"Pasaniuc","sequence":"additional","affiliation":[{"name":"Departments of Pathology and Lab Medicine, University of California , Los Angeles, Los Angeles, CA 90095, USA"}]},{"given":"Hugues","family":"Aschard","sequence":"additional","affiliation":[{"name":"Groupe de G\u00e9n\u00e9tique Statistique, D\u00e9partement de G\u00e9nomes and G\u00e9n\u00e9tique, C3BI, Institut Pasteur , Paris, France"}]}],"member":"286","published-online":{"date-parts":[[2019,6,7]]},"reference":[{"key":"2023013108333803100_btz466-B1","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/nature11632","article-title":"An integrated map of genetic variation from 1, 092 human genomes","volume":"491","author":"Abecasis","year":"2012","journal-title":"Nature"},{"key":"2023013108333803100_btz466-B2","doi-asserted-by":"crossref","first-page":"2925","DOI":"10.1093\/bioinformatics\/btt500","article-title":"DIST: direct imputation of summary statistics for unmeasured SNPs","volume":"29","author":"Lee","year":"2013","journal-title":"Bioinformatics"},{"key":"2023013108333803100_btz466-B3","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1111\/biom.12735","article-title":"Multiple phenotype association tests using summary statistics in genome-wide association studies","volume":"74","author":"Liu","year":"2018","journal-title":"Biometrics"},{"key":"2023013108333803100_btz466-B4","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1038\/nrg.2016.142","article-title":"Dissecting the genetics of complex traits using summary association statistics","volume":"18","author":"Pasaniuc","year":"2017","journal-title":"Nat. Rev. Genet"},{"key":"2023013108333803100_btz466-B5","doi-asserted-by":"crossref","first-page":"2906","DOI":"10.1093\/bioinformatics\/btu416","article-title":"Fast and accurate imputation of summary statistics enhances evidence of functional enrichment","volume":"30","author":"Pasaniuc","year":"2014","journal-title":"Bioinformatics"},{"key":"2023013108333803100_btz466-B6","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1038\/s41588-017-0009-4","article-title":"Multi-trait analysis of genome-wide association summary statistics using MTAG","volume":"50","author":"Turley","year":"2018","journal-title":"Nat. Genet"},{"key":"2023013108333803100_btz466-B7","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1038\/s41588-018-0099-7","article-title":"Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases","volume":"50","author":"Verbanck","year":"2018","journal-title":"Nat. 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Genet"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btz466\/28856172\/btz466.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/22\/4837\/48977736\/bioinformatics_35_22_4837.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/22\/4837\/48977736\/bioinformatics_35_22_4837.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T12:43:42Z","timestamp":1675169022000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/35\/22\/4837\/5512360"}},"subtitle":[],"editor":[{"given":"Russell","family":"Schwartz","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2019,6,7]]},"references-count":8,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2019,11,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btz466","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/502880","asserted-by":"object"}]},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2019,11,15]]},"published":{"date-parts":[[2019,6,7]]}}}