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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
-----
```python
import sys
import vcfnp
import numpy as np
import matplotlib.pyplot as plt
filename = '/path/to/my.vcf'
# load data from fixed fields (except 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))
# load data from INFO field
i = vcfnp.info(filename).view(np.recarray)
# plot a histogram of variant depth
fig = plt.figure(1)
ax = fig.add_subplot(111)
ax.hist(i.DP)
ax.set_title('DP histogram')
ax.set_xlabel('DP')
plt.show()
# load data from sample columns
c = vcfnp.calldata(filename).view(np.recarray)
c = vcfnp.view2d(c)
# print some simple genotype metrics
count_phased = np.count_nonzero(c.is_phased)
count_variant = np.count_nonzero(np.any(c.genotype > 0, axis=2))
count_missing = np.count_nonzero(~c.is_called)
print 'calls (phased, variant, missing): %s (%s, %s, %s)' % (c.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(c.GQ.flatten())
ax.set_title('GQ histogram')
ax.set_xlabel('GQ')
plt.show()
```
Acknowledgments
---------------
Based on the https://github.com/ekg/vcflib library.
=====
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
-----
```python
import sys
import vcfnp
import numpy as np
import matplotlib.pyplot as plt
filename = '/path/to/my.vcf'
# load data from fixed fields (except 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))
# load data from INFO field
i = vcfnp.info(filename).view(np.recarray)
# plot a histogram of variant depth
fig = plt.figure(1)
ax = fig.add_subplot(111)
ax.hist(i.DP)
ax.set_title('DP histogram')
ax.set_xlabel('DP')
plt.show()
# load data from sample columns
c = vcfnp.calldata(filename).view(np.recarray)
c = vcfnp.view2d(c)
# print some simple genotype metrics
count_phased = np.count_nonzero(c.is_phased)
count_variant = np.count_nonzero(np.any(c.genotype > 0, axis=2))
count_missing = np.count_nonzero(~c.is_called)
print 'calls (phased, variant, missing): %s (%s, %s, %s)' % (c.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(c.GQ.flatten())
ax.set_title('GQ histogram')
ax.set_xlabel('GQ')
plt.show()
```
Acknowledgments
---------------
Based on the https://github.com/ekg/vcflib library.
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