Efficient population-scale variant analysis and prioritization with VAPr

1Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

With the growing availability of population-scale whole-exome and whole-genome sequencing, demand for reproducible, scalable variant analysis has spread within genomic research communities. To address this need, we introduce the Python package Variant Analysis and Prioritization (VAPr). VAPr leverages existing annotation tools ANNOVAR and MyVariant.info with MongoDB-based flexible storage and filtering functionality. It offers biologists and bioinformatics generalists easy-to-use and scalable analysis and prioritization of genomic variants from large cohort studies. Availability and implementation: VAPr is developed in Python and is available for free use and extension under the MIT License. An install package is available on PyPi at https://pypi.python.org/pypi/VAPr, while source code and extensive documentation are on GitHub at https://github.com/ucsd-ccbb/VAPr.

Cite

CITATION STYLE

APA

Birmingham, A., Mark, A. M., Mazzaferro, C., Xu, G., & Fisch, K. M. (2018). Efficient population-scale variant analysis and prioritization with VAPr. Bioinformatics, 34(16), 2843–2845. https://doi.org/10.1093/bioinformatics/bty192

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free