<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lopez, Javier</style></author><author><style face="normal" font="default" size="100%">Coll, Jacobo</style></author><author><style face="normal" font="default" size="100%">Haimel, Matthias</style></author><author><style face="normal" font="default" size="100%">Kandasamy, Swaathi</style></author><author><style face="normal" font="default" size="100%">Tárraga, Joaquín</style></author><author><style face="normal" font="default" size="100%">Furio-Tari, Pedro</style></author><author><style face="normal" font="default" size="100%">Bari, Wasim</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Rueda, Antonio</style></author><author><style face="normal" font="default" size="100%">Gräf, Stefan</style></author><author><style face="normal" font="default" size="100%">Rendon, Augusto</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">HGVA: the Human Genome Variation Archive.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Jul 03</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkx445</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">45</style></volume><pages><style face="normal" font="default" size="100%">W189-W194</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;High-profile genomic variation projects like the 1000 Genomes project or the Exome Aggregation Consortium, are generating a wealth of human genomic variation knowledge which can be used as an essential reference for identifying disease-causing genotypes. However, accessing these data, contrasting the various studies and integrating those data in downstream analyses remains cumbersome. The Human Genome Variation Archive (HGVA) tackles these challenges and facilitates access to genomic data for key reference projects in a clean, fast and integrated fashion. HGVA provides an efficient and intuitive web-interface for easy data mining, a comprehensive RESTful API and client libraries in Python, Java and JavaScript for fast programmatic access to its knowledge base. HGVA calculates population frequencies for these projects and enriches their data with variant annotation provided by CellBase, a rich and fast annotation solution. HGVA serves as a proof-of-concept of the genome analysis developments being carried out by the University of Cambridge together with UK's 100 000 genomes project and the National Institute for Health Research BioResource Rare-Diseases, in particular, deploying open-source for Computational Biology (OpenCB) software platform for storing and analyzing massive genomic datasets.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">W1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28535294?dopt=Abstract</style></custom1></record></records></xml>