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GTF.py is a simple module for reading GTF and GFF files
#!/usr/bin/env python
"""
GTF.py
Kamil Slowikowski
December 24, 2013
Read GFF/GTF files. Works with gzip compressed files and pandas.
http://useast.ensembl.org/info/website/upload/gff.html
LICENSE
This is free and unencumbered software released into the public domain.
Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.
In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit
of the public at large and to the detriment of our heirs and
successors. We intend this dedication to be an overt act of
relinquishment in perpetuity of all present and future rights to this
software under copyright law.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
For more information, please refer to <http://unlicense.org/>
"""
from collections import defaultdict
import gzip
import pandas as pd
import re
GTF_HEADER = ['seqname', 'source', 'feature', 'start', 'end', 'score',
'strand', 'frame']
R_SEMICOLON = re.compile(r'\s*;\s*')
R_COMMA = re.compile(r'\s*,\s*')
R_KEYVALUE = re.compile(r'(\s+|\s*=\s*)')
def dataframe(filename):
"""Open an optionally gzipped GTF file and return a pandas.DataFrame.
"""
# Each column is a list stored as a value in this dict.
result = defaultdict(list)
for i, line in enumerate(lines(filename)):
for key in line.keys():
# This key has not been seen yet, so set it to None for all
# previous lines.
if key not in result:
result[key] = [None] * i
# Ensure this row has some value for each column.
for key in result.keys():
result[key].append(line.get(key, None))
return pd.DataFrame(result)
def lines(filename):
"""Open an optionally gzipped GTF file and generate a dict for each line.
"""
fn_open = gzip.open if filename.endswith('.gz') else open
with fn_open(filename) as fh:
for line in fh:
if line.startswith('#'):
continue
else:
yield parse(line)
def parse(line):
"""Parse a single GTF line and return a dict.
"""
result = {}
fields = line.rstrip().split('\t')
for i, col in enumerate(GTF_HEADER):
result[col] = _get_value(fields[i])
# INFO field consists of "key1=value;key2=value;...".
infos = [x for x in re.split(R_SEMICOLON, fields[8]) if x.strip()]
for i, info in enumerate(infos, 1):
# It should be key="value".
try:
key, _, value = re.split(R_KEYVALUE, info, 1)
# But sometimes it is just "value".
except ValueError:
key = 'INFO{}'.format(i)
value = info
# Ignore the field if there is no value.
if value:
result[key] = _get_value(value)
return result
def _get_value(value):
if not value:
return None
# Strip double and single quotes.
value = value.strip('"\'')
# Return a list if the value has a comma.
if ',' in value:
value = re.split(R_COMMA, value)
# These values are equivalent to None.
elif value in ['', '.', 'NA']:
return None
return value
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hindlem Mar 13, 2015

Nice code two suggestions.
Line 70 causes problems when the key:value pair sequence ends in a ; leaving a blank string at the end of infos
infos = [x for x in re.split(R_SEMICOLON, fields[8]) if len(x.strip()) > 0]
Line 75 fails when there is a \s in a value...this is easily fixed by restricting the split to the first instance
key, _, value = re.split(R_KEYVALUE, info, 1)

hindlem commented Mar 13, 2015

Nice code two suggestions.
Line 70 causes problems when the key:value pair sequence ends in a ; leaving a blank string at the end of infos
infos = [x for x in re.split(R_SEMICOLON, fields[8]) if len(x.strip()) > 0]
Line 75 fails when there is a \s in a value...this is easily fixed by restricting the split to the first instance
key, _, value = re.split(R_KEYVALUE, info, 1)

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slowkow Aug 4, 2015

Hi @hindlem, thanks for the suggestions -- they're now in my code.

(I didn't notice your comment until now because github doesn't notify the gist author about comments.)

Owner

slowkow commented Aug 4, 2015

Hi @hindlem, thanks for the suggestions -- they're now in my code.

(I didn't notice your comment until now because github doesn't notify the gist author about comments.)

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vmesel Aug 4, 2016

Pretty awesome code! Going to put it into my lib!

vmesel commented Aug 4, 2016

Pretty awesome code! Going to put it into my lib!

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dyl4nm4rsh4ll Jan 25, 2018

Might I suggest pandas instead?

GFF3 = pd.read_csv(
    filepath_or_buffer=gff3_dir + 'Saccharomyces_cerevisiae.R64-1-1.91.gff3', 
    sep='\t', 
    header=None,
    names=['seqid', 'source', 'type', 'start', 'end', 'score', 'strand', 'phase', 'attributes'],
    skiprows=[i for i in xrange(25)])

GFF3 = GFF3[GFF3['source'].notnull()]

dyl4nm4rsh4ll commented Jan 25, 2018

Might I suggest pandas instead?

GFF3 = pd.read_csv(
    filepath_or_buffer=gff3_dir + 'Saccharomyces_cerevisiae.R64-1-1.91.gff3', 
    sep='\t', 
    header=None,
    names=['seqid', 'source', 'type', 'start', 'end', 'score', 'strand', 'phase', 'attributes'],
    skiprows=[i for i in xrange(25)])

GFF3 = GFF3[GFF3['source'].notnull()]
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slowkow Jan 25, 2018

Dylan, my code should be able to handle lots of different types of GTF or GFF files and automatically parse the key=value items. The pandas read_csv function will not do this.

Owner

slowkow commented Jan 25, 2018

Dylan, my code should be able to handle lots of different types of GTF or GFF files and automatically parse the key=value items. The pandas read_csv function will not do this.

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