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Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts
BACKGROUND: Data from a plethora of high-throughput sequencing studies is readily available to researchers, providing genetic variants detected in a variety of healthy and disease populations. While each individual cohort helps gain insights into polymorphic and disease-associated variants, a joint...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4706706/ https://www.ncbi.nlm.nih.gov/pubmed/26746786 http://dx.doi.org/10.1186/s12859-015-0865-9 |
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author | Hakenberg, Jörg Cheng, Wei-Yi Thomas, Philippe Wang, Ying-Chih Uzilov, Andrew V. Chen, Rong |
author_facet | Hakenberg, Jörg Cheng, Wei-Yi Thomas, Philippe Wang, Ying-Chih Uzilov, Andrew V. Chen, Rong |
author_sort | Hakenberg, Jörg |
collection | PubMed |
description | BACKGROUND: Data from a plethora of high-throughput sequencing studies is readily available to researchers, providing genetic variants detected in a variety of healthy and disease populations. While each individual cohort helps gain insights into polymorphic and disease-associated variants, a joint perspective can be more powerful in identifying polymorphisms, rare variants, disease-associations, genetic burden, somatic variants, and disease mechanisms. DESCRIPTION: We have set up a Reference Variant Store (RVS) containing variants observed in a number of large-scale sequencing efforts, such as 1000 Genomes, ExAC, Scripps Wellderly, UK10K; various genotyping studies; and disease association databases. RVS holds extensive annotations pertaining to affected genes, functional impacts, disease associations, and population frequencies. RVS currently stores 400 million distinct variants observed in more than 80,000 human samples. CONCLUSIONS: RVS facilitates cross-study analysis to discover novel genetic risk factors, gene–disease associations, potential disease mechanisms, and actionable variants. Due to its large reference populations, RVS can also be employed for variant filtration and gene prioritization. AVAILABILITY: A web interface to public datasets and annotations in RVS is available at https://rvs.u.hpc.mssm.edu/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0865-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4706706 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-47067062016-01-10 Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts Hakenberg, Jörg Cheng, Wei-Yi Thomas, Philippe Wang, Ying-Chih Uzilov, Andrew V. Chen, Rong BMC Bioinformatics Database BACKGROUND: Data from a plethora of high-throughput sequencing studies is readily available to researchers, providing genetic variants detected in a variety of healthy and disease populations. While each individual cohort helps gain insights into polymorphic and disease-associated variants, a joint perspective can be more powerful in identifying polymorphisms, rare variants, disease-associations, genetic burden, somatic variants, and disease mechanisms. DESCRIPTION: We have set up a Reference Variant Store (RVS) containing variants observed in a number of large-scale sequencing efforts, such as 1000 Genomes, ExAC, Scripps Wellderly, UK10K; various genotyping studies; and disease association databases. RVS holds extensive annotations pertaining to affected genes, functional impacts, disease associations, and population frequencies. RVS currently stores 400 million distinct variants observed in more than 80,000 human samples. CONCLUSIONS: RVS facilitates cross-study analysis to discover novel genetic risk factors, gene–disease associations, potential disease mechanisms, and actionable variants. Due to its large reference populations, RVS can also be employed for variant filtration and gene prioritization. AVAILABILITY: A web interface to public datasets and annotations in RVS is available at https://rvs.u.hpc.mssm.edu/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0865-9) contains supplementary material, which is available to authorized users. BioMed Central 2016-01-08 /pmc/articles/PMC4706706/ /pubmed/26746786 http://dx.doi.org/10.1186/s12859-015-0865-9 Text en © Hakenberg et al. 2015 Open Access This 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 | Database Hakenberg, Jörg Cheng, Wei-Yi Thomas, Philippe Wang, Ying-Chih Uzilov, Andrew V. Chen, Rong Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts |
title | Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts |
title_full | Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts |
title_fullStr | Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts |
title_full_unstemmed | Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts |
title_short | Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts |
title_sort | integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4706706/ https://www.ncbi.nlm.nih.gov/pubmed/26746786 http://dx.doi.org/10.1186/s12859-015-0865-9 |
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