TY - JOUR
T1 - Integrating 400 million variants from 80,000 human samples with extensive annotations
T2 - Towards a knowledge base to analyze disease cohorts
AU - Hakenberg, Jörg
AU - Cheng, Wei Yi
AU - Thomas, Philippe
AU - Wang, Ying Chih
AU - Uzilov, Andrew V.
AU - Chen, Rong
N1 - Publisher Copyright:
© 2015 Hakenberg et al.
PY - 2016/1/8
Y1 - 2016/1/8
N2 - 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/.
AB - 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/.
KW - Database
KW - Genetics
KW - Variant annotation
UR - http://www.scopus.com/inward/record.url?scp=84953398539&partnerID=8YFLogxK
U2 - 10.1186/s12859-015-0865-9
DO - 10.1186/s12859-015-0865-9
M3 - Article
C2 - 26746786
AN - SCOPUS:84953398539
SN - 1471-2105
VL - 17
JO - BMC Bioinformatics
JF - BMC Bioinformatics
IS - 1
M1 - 24
ER -