genomvar 0.1.11

Sequence variant analysis in Python

Package genomvar works with genomic variants and implements set-like operations on them. The package is inspired by Python data analysis toolkit (NumPy, Pandas) and has a goal to bring that data analysis infrastructure into the field of sequence variant analysis.

For documentation see here.

Installation

Requirements:

1. bx-python 3. jinja2 4. pysam

To install:

pip3 install genomvar

Sample usage

Case 1

Common task in genome variant analysis is: there are two VCF files (for example obtained from variant caller #1 and caller #2) and the differences should be investigated.

First we read the VCF files into genomvar VariantSet objects which hold the variants with underlying data contained in INFO fields:

>>> from genomvar.varset import VariantSet
>>> vs1 = VariantSet.from_vcf('caller1.out.vcf.gz',parse_info=True)
>>> vs2 = VariantSet.from_vcf('caller2.out.vcf.gz',parse_info=True)

To find variants detected by caller #1 but not caller #2 diff method is used. Then differences are exported to numpy for futher analysis:

>>> diff = vs1.diff(vs2)
>>> recs = diff.to_records() # recs is a numpy structured dtype array
>>> recs[['chrom','start','end','ref','alt','vartype']]
[('chr1',  1046755,  1046756, 'T', 'G', 'SNP')
 ('chr1',  1057987,  1057988, 'T', 'C', 'SNP')
  ...,
 ('chr19', 56434340, 56434341, 'A', 'G', 'SNP')
 ('chrY', 56839067, 56839068, 'A', 'G', 'SNP')]
>>> recs['INFO']['DP'].mean() # recs['INFO']['DP'] is a numpy ndarray
232.18819746028257

Case 2

There is a smaller variant file obtained from the data and a bigger one usually obtained from a database. Variants in the former should be “annotated” with some data associated with variants in the latter.

This case is different from the previous in that DB file might not comfortably fit into memory. Class IndexedVariantFileSet can be used for this purpose:

>>> vs = varset.VariantSet.from_vcf('vcf_of_interest.vcf')
>>> dbSNP = varset.IndexedVariantFileSet('DBSNP.vcf.gz')
>>> annots = []
>>> for vrt in vs.iter_vrt():
>>>     m = dbSNP.match(vrt)
>>>     annots.append(m[0].attrib['id'] if m else None)
>>> annots
[None, None, 'rs540057607', 'rs367710686', 'rs940651103', ...]

Here match method is used. It searches for variants with the same genomic alteration as argument variant and returns a list of those. Then VCF ID field can be accessed from those matching variants in attrib['id'] (dbSNP rs numbers in this particular case).