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Convert gVCF into BED

Project description

This is a small tool to convert a gVCF file to BED. This is useful for extracting regions that pass a certain genotype quality threshold.

Installation

gvcf2bed is now available through pypi with: pip install gvcf2bed

Requirements

  • Python 3.4+
  • pyvcf
  • cyvcf2

For developers

  • pytest
  • pytest-cov

Changelog

0.3

  • Use cyvcf2 by default in tool. This results in a speed-up of approximately 8-10x. Existing API has not changed, and will still work with pyvcf.
  • Add separate filter for non-variants, as GQ scores may have a different distribution on non-variant records than on variant records.

Usage

usage: gvcf2bed [-h] -I INPUT -O OUTPUT [-s SAMPLE] [-q QUALITY]
                [-nq NON_VARIANT_QUALITY] [-b]

Create a BED file from a gVCF. Regions are based on a minimum genotype
quality. The gVCF file must contain a GQ field in its FORMAT fields. GQ scores
of non-variants records have a different distribution from the GQ score
distribution of variant records. Hence, an option is provided to set a
different threshold for non-variant positions.

optional arguments:
  -h, --help            show this help message and exit
  -I INPUT, --input INPUT
                        Input gVCF
  -O OUTPUT, --output OUTPUT
                        Output bed file
  -s SAMPLE, --sample SAMPLE
                        Sample name in VCF file to use. Will default to first
                        sample (alphabetically) if not supplied
  -q QUALITY, --quality QUALITY
                        Minimum genotype quality (default 20)
  -nq NON_VARIANT_QUALITY, --non-variant-quality NON_VARIANT_QUALITY
                        Minimum genotype quality for non-variant records
                        (default 20)
  -b, --bedgraph        Output in bedgraph mode

Project details


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0.3

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0.2

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Filename, size & hash SHA256 hash help File type Python version Upload date
gvcf2bed-0.3-py3-none-any.whl (5.9 kB) Copy SHA256 hash SHA256 Wheel py3 Jun 8, 2017
gvcf2bed-0.3.tar.gz (5.0 kB) Copy SHA256 hash SHA256 Source None Jun 8, 2017

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