Literature DB >> 29659724

Efficient population-scale variant analysis and prioritization with VAPr.

Amanda Birmingham1, Adam M Mark1, Carlo Mazzaferro1, Guorong Xu1, Kathleen M Fisch1.   

Abstract

Summary: 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.

Mesh:

Year:  2018        PMID: 29659724      PMCID: PMC6084604          DOI: 10.1093/bioinformatics/bty192

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


  9 in total

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5.  High-performance web services for querying gene and variant annotation.

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8.  GWAS Central: a comprehensive resource for the comparison and interrogation of genome-wide association studies.

Authors:  Tim Beck; Robert K Hastings; Sirisha Gollapudi; Robert C Free; Anthony J Brookes
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9.  A survey of tools for variant analysis of next-generation genome sequencing data.

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1.  Biological Interpretation of Complex Genomic Data.

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