{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T13:43:19Z","timestamp":1775050999471,"version":"3.50.1"},"reference-count":8,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      <jats:italic>ImputAccur<\/jats:italic>\n                      is a software tool to measure genotype-imputation accuracy. Imputation of untyped markers is a standard approach in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy for imputed genotypes is fundamental. Several accuracy measures have been proposed, but unfortunately, they are implemented on different platforms, which is impractical.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      With\n                      <jats:italic>ImputAccur,<\/jats:italic>\n                      the accuracy measures\n                      <jats:italic>info, Iam-hiQ<\/jats:italic>\n                      and\n                      <jats:italic>r<\/jats:italic>\n                      <jats:sup>\n                        <jats:italic>2<\/jats:italic>\n                      <\/jats:sup>\n                      <jats:italic>-based<\/jats:italic>\n                      indices can be derived from standard output files of imputation software. Sample\/probe and marker filtering is possible. This allows e.g. accurate marker filtering ahead of data analysis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      The source code (Python version 3.9.4), a standalone executive file, and example data for\n                      <jats:italic>ImputAccur<\/jats:italic>\n                      are freely available at\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/gitlab.gwdg.de\/kolja.thormann1\/imputationquality.git\">https:\/\/gitlab.gwdg.de\/kolja.thormann1\/imputationquality.git<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-022-04863-z","type":"journal-article","created":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T05:04:10Z","timestamp":1659589450000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["ImputAccur: fast and user-friendly calculation of genotype-imputation accuracy-measures"],"prefix":"10.1186","volume":"23","author":[{"given":"Kolja A.","family":"Thormann","sequence":"first","affiliation":[]},{"given":"Viola","family":"Tozzi","sequence":"additional","affiliation":[]},{"given":"Paula","family":"Starke","sequence":"additional","affiliation":[]},{"given":"Heike","family":"Bickeb\u00f6ller","sequence":"additional","affiliation":[]},{"given":"Marcus","family":"Baum","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7848-1332","authenticated-orcid":false,"given":"Albert","family":"Rosenberger","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,8,4]]},"reference":[{"key":"4863_CR1","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1007\/978-1-62703-447-0_17","volume":"1019","author":"JM Hickey","year":"2013","unstructured":"Hickey JM, Cleveland MA, Maltecca C, Gorjanc G, Gredler B, Kranis A. Genotype imputation to increase sample size in pedigreed populations. Methods Mol Biol. 2013;1019:395\u2013410.","journal-title":"Methods Mol Biol"},{"issue":"19","key":"4863_CR2","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1146\/annurev-genom-083117-021602","volume":"31","author":"S Das","year":"2018","unstructured":"Das S, Abecasis GR, Browning BL. Genotype imputation from large reference panels. Annu Rev Genom Hum Genet. 2018;31(19):73\u201396.","journal-title":"Annu Rev Genom Hum Genet"},{"issue":"7","key":"4863_CR3","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1038\/nrg2796","volume":"11","author":"J Marchini","year":"2010","unstructured":"Marchini J, Howie B. Genotype imputation for genome-wide association studies. Nat Rev Genet. 2010;11(7):499\u2013511.","journal-title":"Nat Rev Genet"},{"issue":"5","key":"4863_CR4","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1038\/nprot.2014.071","volume":"9","author":"TW Winkler","year":"2014","unstructured":"Winkler TW, Day FR, Croteau-Chonka DC, Wood AR, Locke AE, Magi R. Quality control and conduct of genome-wide association meta-analyses. Nat Protoc. 2014;9(5):1192\u2013212.","journal-title":"Nat Protoc"},{"issue":"2","key":"4863_CR5","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1016\/j.ajhg.2009.01.005","volume":"84","author":"BL Browning","year":"2009","unstructured":"Browning BL, Browning SR. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am J Hum Genet. 2009;84(2):210\u201323.","journal-title":"Am J Hum Genet"},{"issue":"1","key":"4863_CR6","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1186\/s12859-022-04568-3","volume":"23","author":"A Rosenberger","year":"2022","unstructured":"Rosenberger A, Tozzi V, Bickeb\u00f6ller H, Hung RJ, Christiani DC, Caporaso NE. Iam hiQ\u2014a novel pair of accuracy indices for imputed genotypes. BMC Bioinform. 2022;23(1):50.","journal-title":"BMC Bioinform"},{"issue":"7","key":"4863_CR7","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1038\/ejhg.2017.51","volume":"25","author":"M Mitt","year":"2017","unstructured":"Mitt M, Kals M, Parn K, Gabriel SB, Lander ES, Palotie A. Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel. Eur J Hum Genet. 2017;25(7):869\u201376.","journal-title":"Eur J Hum Genet"},{"key":"4863_CR8","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1186\/1755-8794-5-12","volume":"5","author":"S Krithika","year":"2012","unstructured":"Krithika S, Valladares-Salgado A, Peralta J, Escobedo-de LaPena J, Kumate-Rodriguez J, Cruz M. Evaluation of the imputation performance of the program IMPUTE in an admixed sample from Mexico City using several model designs. BMC Med Genom. 2012;5:12.","journal-title":"BMC Med Genom"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04863-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-022-04863-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04863-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T05:04:15Z","timestamp":1659589455000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-022-04863-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,4]]},"references-count":8,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["4863"],"URL":"https:\/\/doi.org\/10.1186\/s12859-022-04863-z","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2022.03.07.483268","asserted-by":"object"}]},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,4]]},"assertion":[{"value":"28 April 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 July 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 August 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The example data presented in Fig.\u00a0\n                      \n                      are from the International Lung Cancer Consortium (ILCCO)\/Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL)). All consortium research received approval from the Dartmouth Committee for Protection of Human Subjects on 7\/30\/2014 with id STUDY00023602. Informed consent was obtained from all participants or, if participants are under 18, from a parent and\/or legal guardian. All experimental protocols and other methods used comply with institutional, national, or international guidelines.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"316"}}