Integrating 400 million variants from 80,000 human samples with extensive annotations: towards a knowledge base to analyze disease cohorts

BMC Bioinformatics

Database

Ying-Chih Wang¹  Rong Chen²  Andrew V. Uzilov²  Jörg Hakenberg²  Wei-Yi Cheng³  Philippe Thomas⁴ 

[1] Department of Computer Science, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany;Current affiliation: German Research Centre for Artificial Intelligence (DFKI), Alt Moabit 91c, 10559, Berlin, Germany;Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Box 1498, 10029, New York, USA;Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Box 1498, 10029, New York, USA;Current affiliation: Illumina, Inc., 451 El Camino Real, Suite 210, 95050, Santa Clara, USA;Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Box 1498, 10029, New York, USA;Current affiliation: Roche Parma Research and Early Development, Informatics, Roche Innovation Center New York, 430 East 29th St, 10016, New York, USA;

关键词: Genetics;    Variant annotation;    Database;   

DOI  :  10.1186/s12859-015-0865-9

 received in 2015-07-11, accepted in 2015-12-17,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundData 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.DescriptionWe 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.ConclusionsRVS 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.AvailabilityA web interface to public datasets and annotations in RVS is available at https://rvs.u.hpc.mssm.edu/.

【 授权许可】

CC BY   
© Hakenberg et al. 2015