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.
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 multiple snapshots.
Released under the Apache License, 2.0.
- Timestamped, read-only snapshots.
- Space-efficient storage of sequences within a single snapshot and across snapshots.
- Bandwidth-efficient transfer incremental updates.
- Fast fetching of sequence slices on chromosome-scale sequences.
- Precomputed digests that may be used as sequence aliases.
- Mappings of external aliases (i.e., accessions or identifiers like NM_013305.4) to sequences.
- Local read-only archive, mirrored from public site, accessed via Python API (see Mirroring documentation)
- Local read-write archive, maintained with command line utility and/or API (see Command Line Interface documentation).
- Docker-based data-only container that may be linked to application container.
- Planned: Docker image that provides REST interface for local or remote access
Technical Quick Peek
Within a single snapshot, sequences are stored non-redundantly and compressed in an add-only journalled filesystem structure. A truncated SHA-512 hash is used to assess uniquness and as an internal id. (The digest is truncated for space efficiency.)
Sequences are compressed using the Block GZipped Format (BGZF)), which enables pysam to provide fast random access to compressed sequences. (Variable compression typically makes random access impossible.)
Sequence files are immutable, thereby enabling the use of hardlinks across snapshots and eliminating redundant transfers (e.g., with rsync).
Each sequence id is associated with a namespaced alias in a sqlite database. Such as <seguid,rvvuhY0FxFLNwf10FXFIrSQ7AvQ>, <NCBI,NP_004009.1>, <gi,5032303>, <ensembl-75ENSP00000354464>, <ensembl-85,ENSP00000354464.4>. The sqlite database is mutable across releases.
For calibration, recent releases that include 3 human genome assemblies (including patches), and full RefSeq sets (NM, NR, NP, NT, XM, and XP) consumes approximately 8GB. The minimum marginal size for additional snapshots is approximately 2GB (for the sqlite database, which is not hardlinked).
For more information, see doc/design.rst.
Reading a sequence repository requires several packages, all of which are available from pypi. Installation should be as simple as pip install biocommons.seqrepo.
Writing sequence files also requires bgzip, which provided in the htslib repo. Ubuntu users should install the tabix package with sudo apt install tabix.
Development and deployments are on Ubuntu. Other systems may work but are not tested. Patches to get other systems working would be welcomed.
On Ubuntu 16.04:
$ sudo apt install -y python3-dev gcc zlib1g-dev tabix $ pip install seqrepo $ sudo mkdir /usr/local/share/seqrepo $ sudo chown $USER /usr/local/share/seqrepo $ seqrepo pull -i 20160906 $ seqrepo show-status -i 20160906 seqrepo 0.2.3.post3.dev8+nb8298bd62283 root directory: /usr/local/share/seqrepo/20160906, 7.9 GB backends: fastadir (schema 1), seqaliasdb (schema 1) sequences: 773587 sequences, 93051609959 residues, 192 files aliases: 5579572 aliases, 5480085 current, 26 namespaces, 773587 sequences $ seqrepo start-shell -i 20160906 In : sr["NC_000001.11"][780000:780020] Out: 'TGGTGGCACGCGCTTGTAGT' # N.B. The following output is edited for simplicity $ seqrepo export -i 20160906 | head -n100 >SHA1:9a2acba3dd7603f... SEGUID:mirLo912A/MppLuS1cUyFMduLUQ Ensembl-85:GENSCAN00000003538 ... MDSPLREDDSQTCARLWEAEVKRHSLEGLTVFGTAVQIHNVQRRAIRAKGTQEAQAELLCRGPRLLDRFLEDACILKEGRGTDTGQHCRGDARISSHLEA SGTHIQLLALFLVSSSDTPPSLLRFCHALEHDIRYNSSFDSYYPLSPHSRHNDDLQTPSSHLGYIITVPDPTLPLTFASLYLGMAPCTSMGSSSMGIFQS QRIHAFMKGKNKWDEYEGRKESWKIRSNSQTGEPTF >SHA1:ca996b263102b1... SEGUID:yplrJjECsVqQufeYy0HkDD16z58 NCBI:XR_001733142.1 gi:1034683989 TTTACGTCTTTCTGGGAATTTATACTGGAAGTATACTTACCTCTGTGCAAAATTGCAAATATATAAGGTAATTCATTCCAGCATTGCTTATATTAGGTTG AACTATGTAACATTGACATTGATGTGAATCAAAAATGGTTGAAGGCTGGCAGTTTCATATGATTCAGCCTATAATAGCAAAAGATTGAAAAAATCCATTA ATACAGTGTGGTTCAAAAAAATTTGTTGTATCAAGGTAAAATAATAGCCTGAATATAATTAAGATAGTCTGTGTATACATCGATGAAAACATTGCCAATA
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