GenomeVIP: a cloud platform for genomic variant discovery and interpretation
- Robert J. Mashl1,
- Adam D. Scott1,
- Kuan-lin Huang1,
- Matthew A. Wyczalkowski1,
- Christopher J. Yoon1,
- Beifang Niu1,
- Erin DeNardo1,
- Venkata D. Yellapantula1,
- Robert E. Handsaker2,
- Ken Chen3,
- Daniel C. Koboldt1,
- Kai Ye1,
- David Fenyö4,
- Benjamin Raphael5,
- Michael C. Wendl1 and
- Li Ding1,6
- 1 Washington University;
- 2 Harvard University;
- 3 University of Texas;
- 4 New York University;
- 5 Brown University
- ↵* Corresponding author; email: lding{at}genome.wustl.edu
Abstract
Identifying genomic variants is a fundamental first step towards the understanding of the role of inherited and acquired variations in disease. The accelerating growth in the corpus of sequencing data that underpins such analysis is making the data-download bottleneck more evident, placing substantial burdens on the research community to keep pace. As a result, the search for alternative approaches to the traditional 'download and analyze' paradigm on local computing resources has led to a rapidly growing demand for cloud-computing solutions for genomics analysis. Here, we introduce the Genome Variant Investigation Platform (GenomeVIP), an open-source framework for performing genomics variant discovery and annotation using cloud- or local high-performance computing infrastructure. GenomeVIP orchestrates the analysis of whole genome and exome sequence data using a set of robust and popular task-specific tools, including VarScan, GATK, Pindel, BreakDancer, Strelka, and Genome STRiP, through a web interface. GenomeVIP has been employed for genomic analysis in large-data projects such as the TCGA PanCanAtlas and in other projects, such as the ICGC Pilots, CPTAC, ICGC-TCGA DREAM Challenges, and the 1000 Genomes SV Project. Here, we demonstrate GenomeVIP's ability to provide high-confidence annotated somatic, germline, and de novo variants of potential biological significance using publicly available datasets.
- Received June 21, 2016.
- Accepted May 3, 2017.
- Published by Cold Spring Harbor Laboratory Press
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