VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment
Author(s) -
Lukas Habegger,
Suganthi Balasubramanian,
David Z. Chen,
Ekta Khurana,
Andrea Sboner,
Arif Harmanci,
Joel Rozowsky,
Declan Clarke,
M Snyder,
Mark Gerstein
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts368
Subject(s) - computer science , annotation , cloud computing , documentation , source code , visualization , genome , computational biology , plug in , software , data mining , biology , genetics , gene , operating system , artificial intelligence
The functional annotation of variants obtained through sequencing projects is generally assumed to be a simple intersection of genomic coordinates with genomic features. However, complexities arise for several reasons, including the differential effects of a variant on alternatively spliced transcripts, as well as the difficulty in assessing the impact of small insertions/deletions and large structural variants. Taking these factors into consideration, we developed the Variant Annotation Tool (VAT) to functionally annotate variants from multiple personal genomes at the transcript level as well as obtain summary statistics across genes and individuals. VAT also allows visualization of the effects of different variants, integrates allele frequencies and genotype data from the underlying individuals and facilitates comparative analysis between different groups of individuals. VAT can either be run through a command-line interface or as a web application. Finally, in order to enable on-demand access and to minimize unnecessary transfers of large data files, VAT can be run as a virtual machine in a cloud-computing environment.
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