Python package for writing and reading a local collection of biological sequences. The repository is non-redundant, compressed, and journalled, making it efficient to store and transfer incremental snapshots.
Project description
Python package for writing and reading a local collection of biological sequences. The repository is non-redundant, compressed, and journalled, making it efficient to store and transfer incremental snapshots.
Features
Space-efficient storage of sequences within a release and across releases
Bandwidth-efficient transfer incremental updates
Fast fetching of sequence slices on chromosome-scale sequences
Provenance data regarding sequence sources and accessions
Precomputed digests that may be used as sequence aliases
For more information, see doc/design.rst.
Expected deployment cases
Local access via Python package, using a repo rsync’d from a remote source or loaded locally
Docker image with REST interface
Installation
seqrepo has been tested only on Ubuntu 14.04 and 16.04. It requires separate installation of the tabix package. It requires sqlite3 >= 3.8.0, which likely precludes early Ubuntu distributions.
On Ubuntu 16.04:
sudo apt install tabix pip install seqrepo
Command line usage
seqrepo includes a command line interface for loading, fetching, and exporting sequences.
Loading
$ SEQREPO_ROOT=/opt/seqrepo/data/2016/0818 $ seqrepo -d $SEQREPO_ROOT init $ seqrepo -v -d $SEQREPO_ROOT load-fasta -n me fasta1.gz fasta2.gz fasta3.gz $ seqrepo -v -d $SEQREPO_ROOT status seqrepo 0.1.0 root directory: /opt/seqrepo/data/2016/0818, 0.2 GB backends: fastadir (schema 1), seqaliasdb (schema 1) sequences: 3 files, 33080 sequences, 110419437 residues aliases: 165481 aliases, 165481 current, 5 namespaces, 33080 sequences
Exporting all sequences
$ seqrepo -v -d $SEQREPO_ROOT export | head >me:sequence1 seguid:EqjiLe... md5:04e8c3c75... sha512:000a70c470f6... sha1:12a8e22d... GTACGCCCCCTCCCCCCGTCCCTATCGGCAGAACCGGAGGCCAACCTTCGCGATCCCTTGCTGCGGGCCCGGAGATCAAACGTGGCCCGCCCCCGGCAGG GCACAGCGCGCTGGGCAACCGCGATCCGGCGCCGGACTGGAGGGGTCGATGCGCGGCGCGCTGGGGCGCACAGGGGACGGAGCCCGGGTCTTGCTCCCCA
API Usage
$ seqrepo -v -d $SEQREPO_ROOT shell
In [10]: %time sr.fetch("NC_000001.10", start=6000000, end=6000200)
CPU times: user 4 ms, sys: 0 ns, total: 4 ms
Wall time: 492 µs
Out[10]: 'GGACAACAGAGGATGAGGTGGGGCCAGCAGAGGGACAGAGAAGAGCTGCCTGCCCTGGAACAGGCAGAAAGCATCCCACGTGCAAGAAAAAGTAGGCCAGCTAGACTTAAAATCAGAACTACCGCTCATCAAAAGATAGTGTAACATTTGGGGTGCTATAATTTTAACATGTCCCCCAAAAGGCATGTGTTGGAAATTTA'
# iterate over unique sequences:
for srec, arec in sr:
pprint.pprint(srec)
pprint.pprint(arec)
# results in records like:
{'added': '2016-08-18 17:40:49',
'alpha': 'ACGT',
'len': 2627,
'relpath': '2016/08/18/1740/1471542046.008535.fa.bgz',
'seq': 'GTACGCCC...',
'seq_id': '000a70c470f637d6e3a76497aac3eabc4f7816be8fe03d15bdbd3504655fd3f6ddb2609aeef5e0edfbea16ae8ab181b704c4bfb3cd4328c57a895e02fe5ab518'}
and
[{'added': '2016-08-18 17:40:49',
'alias': '04e8c3c753dad9c19741cdf81ec2b3d5',
'is_current': 1,
'namespace': 'md5',
'seq_id': '000a70c470f637d6e3a76497aac3eabc4f7816be8fe03d15bdbd3504655fd3f6ddb2609aeef5e0edfbea16ae8ab181b704c4bfb3cd4328c57a895e02fe5ab518',
'seqalias_id': 144388},
{'added': '2016-08-18 17:40:49',
'alias': 'EqjiLeXFeeBT6LIMnbCFQxNqHD8',
'is_current': 1,
'namespace': 'seguid',
'seq_id': '000a70c470f637d6e3a76497aac3eabc4f7816be8fe03d15bdbd3504655fd3f6ddb2609aeef5e0edfbea16ae8ab181b704c4bfb3cd4328c57a895e02fe5ab518',
'seqalias_id': 144389},
{'added': '2016-08-18 17:40:49',
'alias': '12a8e22de5c579e053e8b20c9db08543136a1c3f',
'is_current': 1,
'namespace': 'sha1',
'seq_id': '000a70c470f637d6e3a76497aac3eabc4f7816be8fe03d15bdbd3504655fd3f6ddb2609aeef5e0edfbea16ae8ab181b704c4bfb3cd4328c57a895e02fe5ab518',
'seqalias_id': 144387},
{'added': '2016-08-18 17:40:49',
'alias': '000a70c470f637d6e3a76497aac3eabc4f7816be8fe03d15bdbd3504655fd3f6ddb2609aeef5e0edfbea16ae8ab181b704c4bfb3cd4328c57a895e02fe5ab518',
'is_current': 1,
'namespace': 'sha512',
'seq_id': '000a70c470f637d6e3a76497aac3eabc4f7816be8fe03d15bdbd3504655fd3f6ddb2609aeef5e0edfbea16ae8ab181b704c4bfb3cd4328c57a895e02fe5ab518',
'seqalias_id': 144386},
{'added': '2016-08-18 17:40:49',
'alias': 'NM_013305.4',
'is_current': 1,
'namespace': 'ncbi',
'seq_id': '000a70c470f637d6e3a76497aac3eabc4f7816be8fe03d15bdbd3504655fd3f6ddb2609aeef5e0edfbea16ae8ab181b704c4bfb3cd4328c57a895e02fe5ab518',
'seqalias_id': 144390}]
Fetching existing sequence repositories
TO BE WRITTEN
(General idea: Distribute repository with snapshots via rsync server from public site for manual installation, and use the same source to seed a docker container.)
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