{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T13:39:14Z","timestamp":1790516354217,"version":"4.1.0"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"15","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":556,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Post-sequencing DNA analysis typically consists of read mapping followed by variant calling. Especially for whole genome sequencing, this computational step is very time-consuming, even when using multithreading on a multi-core machine.<\/jats:p>\n               <jats:p>Results: We present Halvade, a framework that enables sequencing pipelines to be executed in parallel on a multi-node and\/or multi-core compute infrastructure in a highly efficient manner. As an example, a DNA sequencing analysis pipeline for variant calling has been implemented according to the GATK Best Practices recommendations, supporting both whole genome and whole exome sequencing. Using a 15-node computer cluster with 360\u00a0CPU cores in total, Halvade processes the NA12878 dataset (human, 100\u2009bp paired-end reads, 50\u00d7 coverage) in &amp;lt;3\u2009h with very high parallel efficiency. Even on a single, multi-core machine, Halvade attains a significant speedup compared with running the individual tools with multithreading.<\/jats:p>\n               <jats:p>Availability and implementation: Halvade is written in Java and uses the Hadoop MapReduce 2.0 API. It supports a wide range of distributions of Hadoop, including Cloudera and Amazon EMR. Its source is available at http:\/\/bioinformatics.intec.ugent.be\/halvade under GPL license.<\/jats:p>\n               <jats:p>Contact: \u00a0jan.fostier@intec.ugent.be<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv179","type":"journal-article","created":{"date-parts":[[2015,3,29]],"date-time":"2015-03-29T03:44:55Z","timestamp":1427600695000},"page":"2482-2488","source":"Crossref","is-referenced-by-count":65,"title":["Halvade: scalable sequence analysis with MapReduce"],"prefix":"10.1093","volume":"31","author":[{"given":"Dries","family":"Decap","sequence":"first","affiliation":[{"name":"1 Department of Information Technology, Ghent University \u2013 iMinds, Gaston Crommenlaan 8 bus 201, 9050 Ghent, Belgium,"},{"name":"2 ExaScience Life Lab, Kapeldreef 75, 3001 Leuven, Belgium,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joke","family":"Reumers","sequence":"additional","affiliation":[{"name":"2 ExaScience Life Lab, Kapeldreef 75, 3001 Leuven, Belgium,"},{"name":"3 Janssen Research & Development, a division of Janssen Pharmaceutica N.V., 2340 Beerse, Belgium,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charlotte","family":"Herzeel","sequence":"additional","affiliation":[{"name":"2 ExaScience Life Lab, Kapeldreef 75, 3001 Leuven, Belgium,"},{"name":"4 Imec, Kapeldreef 75, 3001 Leuven, Belgium, and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pascal","family":"Costanza","sequence":"additional","affiliation":[{"name":"2 ExaScience Life Lab, Kapeldreef 75, 3001 Leuven, Belgium,"},{"name":"5 Intel Corporation Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"Fostier","sequence":"additional","affiliation":[{"name":"1 Department of Information Technology, Ghent University \u2013 iMinds, Gaston Crommenlaan 8 bus 201, 9050 Ghent, Belgium,"},{"name":"2 ExaScience Life Lab, Kapeldreef 75, 3001 Leuven, Belgium,"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2015,3,26]]},"reference":[{"key":"2023051308491705300_btv179-B1","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1145\/1327452.1327492","article-title":"MapReduce: simplified data processing on large clusters","volume":"51","author":"Dean","year":"2008","journal-title":"Commun. 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