Non-redundant, compressed, journalled, file-based storage for biological sequences
Project description
biocommons.seqrepo
SeqRepo is a Python package for storing 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.
Introduction
Specific, named biological sequences provide the reference and coordinate sysstem for communicating variation and consequential phenotypic changes. Several databases of sequences exist, with significant overlap, all using distinct names. Furthermore, these systems are often difficult to install locally.
SeqRepo provides an efficient, non-redundant and indexed storage system for biological sequences. Clients refer to sequences and metadata using familiar identifiers, such as NM_000551.3 or GRCh38:1, or any of several hash-based identifiers. The interface supports fast slicing of arbitrary regions of large sequences.
A "fully-qualified" identifier includes a namespace to disambiguate accessions from different origins or sequence sets (e.g., "1" in GRCh37 and GRCh38). If the namespace is provided, seqrepo uses it as-is; if the namespace is not provided and the unqualified identifier refers to a unique sequence, it is returned; otherwise, the use of ambiguous identifiers raise an error.
SeqRepo favors namespaces from identifiers.org whenever available. Examples include refseq and ensembl.
seqrepo-rest-service provides a REST interface and docker image.
Released under the Apache License, 2.0.
| | | ChangeLog
Citation
Hart RK, Prlić A (2020). SeqRepo: A system for managing local collections of biological sequences. PLoS ONE 15(12): e0239883. https://doi.org/10.1371/journal.pone.0239883
Features
- 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.
Deployments Scenarios
- 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 data-only container that may be linked to application container.
- SeqRepo and refget REST API for local or remote access (see seqrepo-rest-service)
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 docs/design.rst.
Requirements
Reading a sequence repository requires several Python packages, all of which are available from pypi. Installation should be as simple as [pip install biocommons.seqrepo]{.title-ref}.
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.
Mac Developers If you get "xcrun: error: invalid active developer path", you need to install XCode. See this StackOverflow answer.
Quick Start
On Ubuntu 16.04:
$ sudo apt install -y python3-dev gcc zlib1g-dev tabix
(OSX: $ brew install python libpq)
$ pip install seqrepo
$ sudo mkdir -p /usr/local/share/seqrepo
$ sudo chown $USER /usr/local/share/seqrepo
$ seqrepo pull -i 2018-11-26
$ seqrepo show-status -i 2018-11-26
seqrepo 0.2.3.post3.dev8+nb8298bd62283
root directory: /usr/local/share/seqrepo/2018-11-26, 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
# Simple Pythonic interface to sequences
>> from biocommons.seqrepo import SeqRepo
>> sr = SeqRepo("/usr/local/share/seqrepo/latest")
>> sr["NC_000001.11"][780000:780020]
'TGGTGGCACGCGCTTGTAGT'
# Or, use the seqrepo shell for even easier access
$ seqrepo start-shell -i 2018-11-26
In [1]: sr["NC_000001.11"][780000:780020]
Out[1]: 'TGGTGGCACGCGCTTGTAGT'
# N.B. The following output is edited for simplicity
$ seqrepo export -i 2018-11-26 | 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
See Installation and Mirroring for more information.
Environment Variables
SEQREPO_LRU_CACHE_MAXSIZE sets the lru_cache maxsize for the sqlite query response caching. It defaults to 1 million but can also be set to "none" to be unlimited.
SEQREPO_FD_CACHE_MAXSIZE sets the lru_cache size for file handler caching during FASTA sequence retrievals. It defaults to 0 to disable any caching, but can be set to a specific value or "none" to be unlimited. Using a moderate value (>10) will greatly increase performance of sequence retrieval.
Developing
Here's how to get started developing:
make devready
source venv/bin/activate
seqrepo --version
Building a docker image
Docker images are available at https://hub.docker.com/r/biocommons/seqrepo. Tags correspond to the version of data, not the version of seqrepo, because the intent is to make it easy to depend on a local version of seqrepo files. Each docker image is an installation of seqrepo that downloads the corresponding version of seqrepo data. When used in conjunction with docker volumes for persistence, this provides an easy way to incorporate seqrepo data into a docker stack.
Building
cd misc/docker
make 2021-01-29.log # builds and pushes to hub.docker.com (i.e., you need creds)
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