An analytical framework for optimizing variant discovery from personal genomes

Published

February 25, 2015

Author(s)

Justin M. Zook, Gareth Highnam, Jason Wang, Dean Kusler, Vinaya Vijayan, Nir Leibovich, David Mittelman

Abstract

The standardization and performance testing of analysis tools is a prerequisite to widespread adoption of high-throughput sequencing, particularly in the clinic. However, performance testing is currently complicated by the paucity of standards and comparison metrics, as well as the heterogeneity in sequencing platforms, applications, and protocols. We have developed the open and collaborative Genome Comparison and Analytic Testing (GCAT) platform to facilitate development of performance metrics and comparisons of analysis tools across these metrics. Performance is reported through interactive visualizations of benchmark and performance testing data, with support for data slicing and filtering. The platform is freely accessible at http://www.bioplanet.com/gcat.

Citation

Nature Methods

Volume

6

Pub Type

Journals

Download Paper

https://doi.org/10.1038/ncomms7275

Keywords

DNA sequencing, genomics, bioinformatics, Reference Materials

Citation

Zook, J. , Highnam, G. , Wang, J. , Kusler, D. , Vijayan, V. , Leibovich, N. and Mittelman, D. (2015), An analytical framework for optimizing variant discovery from personal genomes, Nature Methods, [online], https://doi.org/10.1038/ncomms7275 (Accessed April 19, 2024)