Alex V. Kotlar, Cristina E. Trevino, M. Zwick, D. Cutler, T. Wingo
{"title":"SeqAnt: Cloud-Based Whole-Genome Annotation and Search","authors":"Alex V. Kotlar, Cristina E. Trevino, M. Zwick, D. Cutler, T. Wingo","doi":"10.1145/3107411.3108231","DOIUrl":null,"url":null,"abstract":"Describing, prioritizing, and selecting alleles from large sequencing experiments remains technically challenging. SeqAnt (https://seqant.emory.edu) is the first online, cloud-based application that makes these tasks accessible for non-programmers, even for terabyte-sized experiments containing thousands of whole-genome samples. It rapidly describes the alleles found within submitted VCF files, and then indexes the results in a natural-language search engine, which enables users to locate alleles of interest in milliseconds using normal English phrases. Our results show that SeqAnt decreases processing time by orders of magnitude and that its search engine can be used to precisely identify alleles by phenotype, genomic structure, and population genetics characteristics.","PeriodicalId":246388,"journal":{"name":"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3107411.3108231","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Describing, prioritizing, and selecting alleles from large sequencing experiments remains technically challenging. SeqAnt (https://seqant.emory.edu) is the first online, cloud-based application that makes these tasks accessible for non-programmers, even for terabyte-sized experiments containing thousands of whole-genome samples. It rapidly describes the alleles found within submitted VCF files, and then indexes the results in a natural-language search engine, which enables users to locate alleles of interest in milliseconds using normal English phrases. Our results show that SeqAnt decreases processing time by orders of magnitude and that its search engine can be used to precisely identify alleles by phenotype, genomic structure, and population genetics characteristics.