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Efficient population-scale variant analysis and prioritization with VAPr
- Source :
- Bioinformatics. 34:2843-2845
- Publication Year :
- 2018
- Publisher :
- Oxford University Press (OUP), 2018.
-
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.
- Subjects :
- 0301 basic medicine
Statistics and Probability
Prioritization
Source code
Computer science
media_common.quotation_subject
Population
030105 genetics & heredity
computer.software_genre
Biochemistry
03 medical and health sciences
Exome
education
Molecular Biology
media_common
computer.programming_language
education.field_of_study
Database
Computational Biology
Genomics
Python (programming language)
Applications Notes
Computer Science Applications
Computational Mathematics
030104 developmental biology
Computational Theory and Mathematics
Metagenomics
computer
Software
Subjects
Details
- ISSN :
- 13674811 and 13674803
- Volume :
- 34
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....a80b28827926e28c3bd00cfc5e8ff57c