Literature DB >> 22743228

VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment.

Lukas Habegger1, Suganthi Balasubramanian, David Z Chen, Ekta Khurana, Andrea Sboner, Arif Harmanci, Joel Rozowsky, Declan Clarke, Michael Snyder, Mark Gerstein.   

Abstract

UNLABELLED: 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.
AVAILABILITY AND IMPLEMENTATION: VAT is implemented in C and PHP. The VAT web service, Amazon Machine Image, source code and detailed documentation are available at vat.gersteinlab.org.

Mesh:

Year:  2012        PMID: 22743228      PMCID: PMC3426844          DOI: 10.1093/bioinformatics/bts368

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


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