/cyvcf2

cython + htslib == fast VCF and BCF processing

Primary LanguageCMIT LicenseMIT

cyvcf2

Docs

If you use cyvcf2, please cite the paper

Fast python (2 and 3) parsing of VCF and BCF including region-queries.

Build Status

cyvcf2 is a cython wrapper around htslib built for fast parsing of Variant Call Format (VCF) files.

Attributes like variant.gt_ref_depths return a numpy array directly so they are immediately ready for downstream use. note that the array is backed by the underlying C data, so, once variant goes out of scope. The array will contain nonsense. To persist a copy, use: cpy = np.array(variant.gt_ref_depths) instead of just arr = variant.gt_ref_depths.

Example

The example below shows much of the use of cyvcf2.

from cyvcf2 import VCF

for variant in VCF('some.vcf.gz'): # or VCF('some.bcf')
	variant.REF, variant.ALT # e.g. REF='A', ALT=['C', 'T']


	variant.CHROM, variant.start, variant.end, variant.ID, \
				variant.FILTER, variant.QUAL

	# numpy arrays of specific things we pull from the sample fields.
	# gt_types is array of 0,1,2,3==HOM_REF, HET, UNKNOWN, HOM_ALT
	variant.gt_types, variant.gt_ref_depths, variant.gt_alt_depths # numpy arrays
	variant.gt_phases, variant.gt_quals, variant.gt_bases # numpy array


	## INFO Field.
	## extract from the info field by it's name:
	variant.INFO.get('DP') # int
	variant.INFO.get('FS') # float
	variant.INFO.get('AC') # float

	# convert back to a string.
	str(variant)


	## sample info...

	# Get a numpy array of the depth per sample:
    dp = variant.format('DP')
    # or of any other format field:
    sb = variant.format('SB')
    assert sb.shape == (n_samples, 4) # 4-values per

# to do a region-query:

vcf = VCF('some.vcf.gz')
for v in vcf('11:435345-556565'):
    if v.INFO["AF"] > 0.1: continue
    print(str(v))

Installation

pip

pip install cyvcf2

github

git clone https://github.com/brentp/cyvcf2
cd cyvcf2
pip install --editable .

Testing

Tests can be run with:

python setup.py test

CLI

Run with cyvcf2 path_to_vcf

$ cyvcf2 --help
Usage: cyvcf2 [OPTIONS] <vcf_file> or -

  fast vcf parsing with cython + htslib

Options:
  -c, --chrom TEXT                Specify what chromosome to include.
  -s, --start INTEGER             Specify the start of region.
  -e, --end INTEGER               Specify the end of the region.
  --include TEXT                  Specify what info field to include.
  --exclude TEXT                  Specify what info field to exclude.
  --loglevel [DEBUG|INFO|WARNING|ERROR|CRITICAL]
                                  Set the level of log output.  [default:
                                  INFO]
  --silent                        Skip printing of vcf.
  --help                          Show this message and exit.

See Also

Pysam also has a cython wrapper to htslib and one block of code here is taken directly from that library. But, the optimizations that we want for gemini are very specific so we have chosen to create a separate project.

Performance

For the performance comparison in the paper, we used thousand genomes chromosome 22 With the full comparison runner here.