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Fast GTF parser

Project description

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Overview
***************************************
We want an extremely fast, lightweight way to access gene data stored in GTF format.

The parsed data is held in an intuitive
Gene
-> transcript
-> transcript
with exons being stored as intervals

Our aim is to
* cache data in binary format, which can be
* re-read in < 10s for even the largest genomes

Currently initial parsing Ensembl Homo sapiens release 56 takes around 4.5 minutes.
The binary data can be reloaded in < 10s.
This contains *all* of the data structure in the original GTF file

Note that we sacrifice memory usage for speed. This is seldom a problem for modern computers
and genome sizes (There are around ~400,000 exons but there are stored as intervals / int pairs)

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A Simple example
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::
gene_structures = t_parse_gtf("Mus musculus")

#
# used cached data for speed
#
ignore_cache = False

#
# get all protein coding genes only
#
genes_by_type = gene_structures.get_genes(gtf_file, logger, ["protein_coding"], ignore_cache = ignore_cache)

#
# print out gene counts
#
t_parse_gtf.log_gene_types (logger, genes_by_type)

return genes_by_type

Project details


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Filename, size & hash SHA256 hash help File type Python version Upload date
gtf_to_genes-1.40.tar.gz (35.6 kB) Copy SHA256 hash SHA256 Source None Dec 4, 2014

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