Load numpy arrays from a VCF (variant call file).
Project description
vcfnp
=====
Load numpy arrays from a VCF (variant call file).
Installation
------------
Installation requires numpy and cython::
$ pip install vcfnp
...or::
$ git clone --recursive git://github.com/alimanfoo/vcfnp.git
$ cd vcfnp
$ python setup.py build_ext --inplace
Usage
-----
::
import sys
import vcfnp
import numpy as np
import matplotlib.pyplot as plt
filename = '/path/to/my.vcf'
# load data from fixed fields (including INFO)
V = vcfnp.variants(filename).view(np.recarray)
# print some simple variant metrics
print 'found %s variants (%s SNPs)' % (v.size, np.count_nonzero(v.is_snp))
print 'QUAL mean (std): %s (%s)' % (np.mean(v.QUAL), np.std(v.QUAL))
# plot a histogram of variant depth
fig = plt.figure(1)
ax = fig.add_subplot(111)
ax.hist(V.DP)
ax.set_title('DP histogram')
ax.set_xlabel('DP')
plt.show()
# load data from sample columns
C = vcfnp.calldata(filename).view(np.recarray)
C2d = vcfnp.view2d(C)
# print some simple genotype metrics
count_phased = np.count_nonzero(C2d.is_phased)
count_variant = np.count_nonzero(np.any(C2d.genotype > 0, axis=2))
count_missing = np.count_nonzero(~C2d.is_called)
print 'calls (phased, variant, missing): %s (%s, %s, %s)' % (C2d.flatten().size, count_phased, count_variant, count_missing)
# plot a histogram of genotype quality
fig = plt.figure(2)
ax = fig.add_subplot(111)
ax.hist(C2d.GQ.flatten())
ax.set_title('GQ histogram')
ax.set_xlabel('GQ')
plt.show()
Release Notes
-------------
* `1.5 <https://github.com/alimanfoo/vcfnp/issues?milestone=1&state=closed>`_
* `1.0 <https://github.com/alimanfoo/vcfnp/issues?milestone=2&page=1&state=closed>`_ - Note that as of version 1.0 the
info() function has been removed and the variants() function now loads data from any of the VCF fixed fields including
INFO. I.e., the variants() function gives access to all variant-level data in a single structured array. This is
convenient for many use cases, e.g., using PyTables in-kernel queries to select variants passing some filtering criteria.
Acknowledgments
---------------
Based on Erik Garrison's `vcflib <https://github.com/ekg/vcflib>`_.
=====
Load numpy arrays from a VCF (variant call file).
Installation
------------
Installation requires numpy and cython::
$ pip install vcfnp
...or::
$ git clone --recursive git://github.com/alimanfoo/vcfnp.git
$ cd vcfnp
$ python setup.py build_ext --inplace
Usage
-----
::
import sys
import vcfnp
import numpy as np
import matplotlib.pyplot as plt
filename = '/path/to/my.vcf'
# load data from fixed fields (including INFO)
V = vcfnp.variants(filename).view(np.recarray)
# print some simple variant metrics
print 'found %s variants (%s SNPs)' % (v.size, np.count_nonzero(v.is_snp))
print 'QUAL mean (std): %s (%s)' % (np.mean(v.QUAL), np.std(v.QUAL))
# plot a histogram of variant depth
fig = plt.figure(1)
ax = fig.add_subplot(111)
ax.hist(V.DP)
ax.set_title('DP histogram')
ax.set_xlabel('DP')
plt.show()
# load data from sample columns
C = vcfnp.calldata(filename).view(np.recarray)
C2d = vcfnp.view2d(C)
# print some simple genotype metrics
count_phased = np.count_nonzero(C2d.is_phased)
count_variant = np.count_nonzero(np.any(C2d.genotype > 0, axis=2))
count_missing = np.count_nonzero(~C2d.is_called)
print 'calls (phased, variant, missing): %s (%s, %s, %s)' % (C2d.flatten().size, count_phased, count_variant, count_missing)
# plot a histogram of genotype quality
fig = plt.figure(2)
ax = fig.add_subplot(111)
ax.hist(C2d.GQ.flatten())
ax.set_title('GQ histogram')
ax.set_xlabel('GQ')
plt.show()
Release Notes
-------------
* `1.5 <https://github.com/alimanfoo/vcfnp/issues?milestone=1&state=closed>`_
* `1.0 <https://github.com/alimanfoo/vcfnp/issues?milestone=2&page=1&state=closed>`_ - Note that as of version 1.0 the
info() function has been removed and the variants() function now loads data from any of the VCF fixed fields including
INFO. I.e., the variants() function gives access to all variant-level data in a single structured array. This is
convenient for many use cases, e.g., using PyTables in-kernel queries to select variants passing some filtering criteria.
Acknowledgments
---------------
Based on Erik Garrison's `vcflib <https://github.com/ekg/vcflib>`_.
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