bioinfo_tools 0.3.1
Installation
pip install bioinfo_toolsParsers
HEADS UP! These parsers are still under development and usage is not consistent from one parser to another.
Fasta parser
from bioinfo_tools.parsers.fasta import FastaParser
fasta_parser = FastaParser()
# by default, sequence IDs are separated by the firstly found '|' or ':'
for seqid, sequence in fasta_parser.read("/path/to/file.fasta"):
print(seqid, sequence)
# you may specify a specific separator for your sequence ID (e.g white space):
for seqid, sequence in fasta_parser.read("/path/to/file.fasta", id_separator=" "):
print(seqid, sequence)GFF parser
from bioinfo_tools.parsers.gff import Gff3
gff_parser = Gff3()
with open("/path/to/file.gff", "r") as fh:
for gene in gff_parser.read(fh):
print(gene)
import gzip
with gzip.open("/path/to/file.gz", "rb") as fh:
for gene in gff_parser.read(fh):
print(gene)OBO parser
from bioinfo_tools.parsers.obo import OboParser
obo_parser = OboParser()
with open("/path/to/file.obo") as fh:
go_terms = obo_parser.read(fh)
for go_term in go_terms.values():
print(go_term)
# you may also get the GO term parents via the parser
parents = obo_parser.get_parents(go_term)Usage Examples
Extract all introns sequences by parsing GFF and fasta files
In this example, we focus on a genome assembly. We will first load a GFF file containing gene annotations for this assembly, then load a fastA file containing the nucleic sequences of each chromosome in the genome. We will then collect all transcript introns and extract their nucleic sequences.
DISCLAIMER: for this example to work, your GFF file must expose at least the following feature types in column #3:
gene- one of
transcript|mRNA|RNA(or lowercased version)
from bioinfo_tools.genomic_features.chromosome import Chromosome
from bioinfo_tools.parsers.gff import Gff3
from bioinfo_tools.parsers.fasta import FastaParser
chromosomes = dict() # {<chromosome_id>: <bioinfo_tools.genomic_features.Chromosome>}
# start with parsing a GFF file
gff_parser = Gff3()
with open("/path/to/gene_models.gff", "r") as fh:
for gene in gff_parser.read(fh):
chromosome = gene['seqid']
if chromosome not in chromosomes:
chromosomes[chromosome] = Chromosome(chromosome) # init a new Chromosome object
chromosomes[chromosome].add_gene(gene) # add the current gene to our Chromosome object
# load our chromosome sequences in memory
fasta_parser = FastaParser()
for chromosome, nucleic_sequence in fasta_parser.read("/path/to/genome_chromosomes.fasta"):
if chromosome not in chromosomes:
chromosomes[chromosome] = Chromosome(chromosome)
# attach parsed chromosome sequence to our Chromosome object
chromosomes[chromosome].attach_nucleic_sequence(nucleic_sequence)
# now, collect introns and extact their nucleic sequence
introns_sequences = dict() # {<intron_id>: <intron_sequence>}
for chromosome in chromosomes.values():
for gene in chromosome.genes:
for transcript in gene.transcripts:
for idx, intron in enumerate(transcript.introns):
intron_id = "%s_intron_%s" % (transcript.transcript_id, idx)
intron_seq = intron.extract(chromosome.nucleic_sequence) # that we attached above
introns_sequences[intron_id] = intron_seq
# from here, you can do what you want with the intron sequences (eg. write them to a fasta file, etc)
# ...Note: when at the transcript level, you can grab its feature types as described in your GFF file by doing so:
for feature in transcript._get_features("exon"):
print(feature) # I'm an exonFor convenience and clarity, following properties are available on transcript objects:
print(transcript.introns) # will call transcript._get_features('intron') behind the scenes
print(transcript.exons) # will call transcript._get_features('exon') behind the scenes
print(transcript.cds) # will call transcript._get_features('cds') behind the scenes
print(transcript.polypeptide) # will call transcript._get_features('polypeptide') behind the scenes
print(transcript.five_prime_utr) # will call transcript._get_features('five_prime_utr') behind the scenes
print(transcript.three_prime_utr) # will call transcript._get_features('three_prime_utr') behind the scenes