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Bioinformatics. 2018 Aug 15;34(16):2843-2845. doi: 10.1093/bioinformatics/bty192.

Efficient population-scale variant analysis and prioritization with VAPr.

Author information

Center for Computational Biology and Bioinformatics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.



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 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, while source code and extensive documentation are on GitHub at

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