def test_fromtabix_noheader():
actual = etl.fromtabix('fixture/test_noheader.bed.gz',
region='Pf3D7_02_v3:110000-120000')
expect = (('Pf3D7_02_v3', '105800', '447300', 'Core'),)
ieq(expect, actual)
def test_fromtabix():
actual = etl.fromtabix('fixture/test.bed.gz',
region='Pf3D7_02_v3:110000-120000')
expect = (('#chrom', 'start', 'end', 'region'),
('Pf3D7_02_v3', '105800', '447300', 'Core'))
ieq(expect, actual)
# -*- coding: utf-8 -*-
from __future__ import absolute_import, print_function, division
# fromtabix()
#############
import petl as etl
# activate bio extensions
import petlx.bio
table1 = etl.fromtabix('fixture/test.bed.gz',
region='Pf3D7_02_v3')
table1
table2 = etl.fromtabix('fixture/test.bed.gz',
region='Pf3D7_02_v3:110000-120000')
table2
# fromgff3()
############
import petl as etl
# activate bio extensions
import petlx.bio
table1 = etl.fromgff3('fixture/sample.gff')
table1.look(truncate=30)
# extract from a specific genome region via tabix
table2 = etl.fromgff3('fixture/sample.sorted.gff.gz',
region='apidb|MAL5:1289593-1289595')
table2.look(truncate=30)
def fromgff3(filename, region=None):
"""
Extract feature rows from a GFF3 file, e.g.::
>>> import petl as etl
>>> # activate bio extensions
... import petlx.bio
>>> table1 = etl.fromgff3('fixture/sample.gff')
>>> table1.look(truncate=30)
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| seqid | source | type | start | end | score | strand | phase | attributes |
+==============+=========+===============+=======+=========+=======+========+=======+================================+
| 'apidb|MAL1' | 'ApiDB' | 'supercontig' | 1 | 643292 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL2' | 'ApiDB' | 'supercontig' | 1 | 947102 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL3' | 'ApiDB' | 'supercontig' | 1 | 1060087 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL4' | 'ApiDB' | 'supercontig' | 1 | 1204112 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL5' | 'ApiDB' | 'supercontig' | 1 | 1343552 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
...
A region query string of the form '[seqid]' or '[seqid]:[start]-[end]'
may be given for the `region` argument. If given, requires the GFF3
file to be position sorted, bgzipped and tabix indexed. Requires pysam to be
installed. E.g.::
>>> # extract from a specific genome region via tabix
... table2 = etl.fromgff3('fixture/sample.sorted.gff.gz',
... region='apidb|MAL5:1289593-1289595')
>>> table2.look(truncate=30)
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
| seqid | source | type | start | end | score | strand | phase | attributes |
+==============+=========+===============+=========+=========+=======+========+=======+================================+
| 'apidb|MAL5' | 'ApiDB' | 'supercontig' | 1 | 1343552 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL5' | 'ApiDB' | 'exon' | 1289594 | 1291685 | '.' | '+' | '.' | {'size': '2092', 'Parent': 'ap |
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL5' | 'ApiDB' | 'gene' | 1289594 | 1291685 | '.' | '+' | '.' | {'ID': 'apidb|MAL5_18S', 'web_ |
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL5' | 'ApiDB' | 'rRNA' | 1289594 | 1291685 | '.' | '+' | '.' | {'ID': 'apidb|rna_MAL5_18S-1', |
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
"""
if region is None:
# parse file as tab-delimited
table = etl.fromtsv(filename)
else:
# extract via tabix
table = etl.fromtabix(filename, region=region)
return (table.pushheader(GFF3_HEADER).skipcomments('#')
# ignore any row not 9 values long (e.g., trailing fasta)
.rowlenselect(9)
# parse attributes into a dict
.convert('attributes', gff3_parse_attributes)
# parse coordinates
.convert(('start', 'end'), int))
def fromgff3(filename, region=None):
"""
Extract feature rows from a GFF3 file, e.g.::
>>> import petl as etl
>>> # activate bio extensions
... import petlx.bio
>>> table1 = etl.fromgff3('fixture/sample.gff')
>>> table1.look(truncate=30)
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| seqid | source | type | start | end | score | strand | phase | attributes |
+==============+=========+===============+=======+=========+=======+========+=======+================================+
| 'apidb|MAL1' | 'ApiDB' | 'supercontig' | 1 | 643292 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL2' | 'ApiDB' | 'supercontig' | 1 | 947102 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL3' | 'ApiDB' | 'supercontig' | 1 | 1060087 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL4' | 'ApiDB' | 'supercontig' | 1 | 1204112 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL5' | 'ApiDB' | 'supercontig' | 1 | 1343552 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+-------+---------+-------+--------+-------+--------------------------------+
...
A region query string of the form '[seqid]' or '[seqid]:[start]-[end]'
may be given for the `region` argument. If given, requires the GFF3
file to be position sorted, bgzipped and tabix indexed. Requires pysam to be
installed. E.g.::
>>> # extract from a specific genome region via tabix
... table2 = etl.fromgff3('fixture/sample.sorted.gff.gz',
... region='apidb|MAL5:1289593-1289595')
>>> table2.look(truncate=30)
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
| seqid | source | type | start | end | score | strand | phase | attributes |
+==============+=========+===============+=========+=========+=======+========+=======+================================+
| 'apidb|MAL5' | 'ApiDB' | 'supercontig' | 1 | 1343552 | '.' | '+' | '.' | {'localization': 'nuclear', 'o |
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL5' | 'ApiDB' | 'exon' | 1289594 | 1291685 | '.' | '+' | '.' | {'size': '2092', 'Parent': 'ap |
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL5' | 'ApiDB' | 'gene' | 1289594 | 1291685 | '.' | '+' | '.' | {'ID': 'apidb|MAL5_18S', 'web_ |
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
| 'apidb|MAL5' | 'ApiDB' | 'rRNA' | 1289594 | 1291685 | '.' | '+' | '.' | {'ID': 'apidb|rna_MAL5_18S-1', |
+--------------+---------+---------------+---------+---------+-------+--------+-------+--------------------------------+
"""
if region is None:
# parse file as tab-delimited
table = etl.fromtsv(filename)
else:
# extract via tabix
table = etl.fromtabix(filename, region=region)
return (
table
.pushheader(GFF3_HEADER)
.skipcomments('#')
# ignore any row not 9 values long (e.g., trailing fasta)
.rowlenselect(9)
# parse attributes into a dict
.convert('attributes', gff3_parse_attributes)
# parse coordinates
.convert(('start', 'end'), int)
)
# -*- coding: utf-8 -*-
from __future__ import absolute_import, print_function, division
# fromtabix()
#############
import petl as etl
# activate bio extensions
import petlx.bio
table1 = etl.fromtabix('fixture/test.bed.gz', region='Pf3D7_02_v3')
table1
table2 = etl.fromtabix('fixture/test.bed.gz',
region='Pf3D7_02_v3:110000-120000')
table2
# fromgff3()
############
import petl as etl
# activate bio extensions
import petlx.bio
table1 = etl.fromgff3('fixture/sample.gff')
table1.look(truncate=30)
# extract from a specific genome region via tabix
table2 = etl.fromgff3('fixture/sample.sorted.gff.gz',
region='apidb|MAL5:1289593-1289595')
table2.look(truncate=30)
# fromvcf()
###########