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Bystro: rapid online variant annotation and natural-language filtering at whole-genome scale
Accurately selecting relevant alleles in large sequencing experiments remains technically challenging. Bystro (https://bystro.io/) is the first online, cloud-based application that makes variant annotation and filtering accessible to all researchers for terabyte-sized whole-genome experiments contai...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801807/ https://www.ncbi.nlm.nih.gov/pubmed/29409527 http://dx.doi.org/10.1186/s13059-018-1387-3 |
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author | Kotlar, Alex V. Trevino, Cristina E. Zwick, Michael E. Cutler, David J. Wingo, Thomas S. |
author_facet | Kotlar, Alex V. Trevino, Cristina E. Zwick, Michael E. Cutler, David J. Wingo, Thomas S. |
author_sort | Kotlar, Alex V. |
collection | PubMed |
description | Accurately selecting relevant alleles in large sequencing experiments remains technically challenging. Bystro (https://bystro.io/) is the first online, cloud-based application that makes variant annotation and filtering accessible to all researchers for terabyte-sized whole-genome experiments containing thousands of samples. Its key innovation is a general-purpose, natural-language search engine that enables users to identify and export alleles and samples of interest in milliseconds. The search engine dramatically simplifies complex filtering tasks that previously required programming experience or specialty command-line programs. Critically, Bystro’s annotation and filtering capabilities are orders of magnitude faster than previous solutions, saving weeks of processing time for large experiments. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1387-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5801807 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58018072018-02-14 Bystro: rapid online variant annotation and natural-language filtering at whole-genome scale Kotlar, Alex V. Trevino, Cristina E. Zwick, Michael E. Cutler, David J. Wingo, Thomas S. Genome Biol Software Accurately selecting relevant alleles in large sequencing experiments remains technically challenging. Bystro (https://bystro.io/) is the first online, cloud-based application that makes variant annotation and filtering accessible to all researchers for terabyte-sized whole-genome experiments containing thousands of samples. Its key innovation is a general-purpose, natural-language search engine that enables users to identify and export alleles and samples of interest in milliseconds. The search engine dramatically simplifies complex filtering tasks that previously required programming experience or specialty command-line programs. Critically, Bystro’s annotation and filtering capabilities are orders of magnitude faster than previous solutions, saving weeks of processing time for large experiments. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1387-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-02-06 /pmc/articles/PMC5801807/ /pubmed/29409527 http://dx.doi.org/10.1186/s13059-018-1387-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Kotlar, Alex V. Trevino, Cristina E. Zwick, Michael E. Cutler, David J. Wingo, Thomas S. Bystro: rapid online variant annotation and natural-language filtering at whole-genome scale |
title | Bystro: rapid online variant annotation and natural-language filtering at whole-genome scale |
title_full | Bystro: rapid online variant annotation and natural-language filtering at whole-genome scale |
title_fullStr | Bystro: rapid online variant annotation and natural-language filtering at whole-genome scale |
title_full_unstemmed | Bystro: rapid online variant annotation and natural-language filtering at whole-genome scale |
title_short | Bystro: rapid online variant annotation and natural-language filtering at whole-genome scale |
title_sort | bystro: rapid online variant annotation and natural-language filtering at whole-genome scale |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801807/ https://www.ncbi.nlm.nih.gov/pubmed/29409527 http://dx.doi.org/10.1186/s13059-018-1387-3 |
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