uta -- Universal Transcript Archive

bringing smiles to transcript users since 2013

The UTA (Universal Transcript Archive) stores transcripts aligned to sequence references (typically genome reference assemblies). It supports aligning the same transcript to multiple references using multiple alignment methods. Specifically, it facilitates the following:

• Querying for multiple transcript sources through a single interface
• Interpreting variants reported in literature against obsolete transcript records
• Identifying regions where transcript and reference genome sequence assemblies disagree
• Comparing transcripts across from distinct sources
• Comparing transcript alignments generated by multiple methods
• Identifying ambiguities in transcript alignments

UTA is used by the hgvs package to map variants between genomic, transcript, and protein coordinates.

This code repository is primarily used for generating the UTA database. The primary interface for the database itself is via direct PostgreSQL access. (A REST interface is planned, but not yet available.)

Users can access a public instance of UTA or build their own instance of the database.

Accessing the Public UTA Instance

Invitae provides a public instance of UTA. The connection parameters are:

param	value
host	uta.biocommons.org
port	5432 (default)
database	uta
login	anonymous
password	anonymous

For example:

$ PGPASSWORD=anonymous psql -h uta.biocommons.org -U anonymous -d uta

Or, in Python (requires psycopg2):

> import psycopg2, psycopg2.extras
> conn = psycopg2.connect("host=uta.biocommons.org dbname=uta user=anonymous password=anonymous")
> cur = conn.cursor(cursor_factory=psycopg2.extras.DictCursor)
> cur.execute("select * from uta_20140210.tx_def_summary_v where hgnc='BRCA1'")
> row = cur.fetchone()
> dict(row)
{'hgnc': 'BRCA1',
'cds_md5': 'b3d16af258a759d0321d4f83b55dd51b',
'es_fingerprint': 'f91ab768a35c8db477fbf04dde6955e2',
'tx_ac': 'ENST00000357654',
'alt_ac': 'ENST00000357654',
'alt_aln_method': 'transcript',
'alt_strand': 1,
'exon_set_id': 7027,
'n_exons': 23,
'se_i': '0,100;100,199;199,253;253,331;331,420;420,560;560,666;666,712;712,789;789,4215;4215,4304;4304,4476;4476,4603;4603,4794;4794,5105;5105,5193;5193,5271;5271,5312;5312,5396;5396,5451;5451,5525;5525,5586;5586,7094',
'starts_i': [0,
100,
199,
253,
331,
420,
560,
666,
712,
789,
4215,
4304,
4476,
4603,
4794,
5105,
5193,
5271,
5312,
5396,
5451,
5525,
5586],
'ends_i': [100,
199,
253,
331,
420,
560,
666,
712,
789,
4215,
4304,
4476,
4603,
4794,
5105,
5193,
5271,
5312,
5396,
5451,
5525,
5586,
7094],
'lengths': [100,
99,
54,
78,
89,
140,
106,
46,
77,
3426,
89,
172,
127,
191,
311,
88,
78,
41,
84,
55,
74,
61,
1508],
'cds_start_i': 119,
'cds_end_i': 5711}

Installing UTA Locally

Installing with Docker (preferred)

Docker enables the distribution of lightweight, isolated packages that run on essentially any platform. When you use this approach, you will end up with a local UTA installation that runs as a local PostgreSQL process. The only requirement is Docker itself - you will not need to install PostgreSQL or any of its dependencies.

1. Install Docker.

2. Define the UTA version to download. A list of available versions can be found here:

   $ uta_v=uta_20210129b
   

   This variable is used only for consistency in the examples that follow. Defining this variable is not required for any other reason.

   The UTA version string indicates the data release date. The tag is made at the time of loading and is used to derive the filename for the database dumps and docker images. Therefore, the public c instances, database dumps, and docker images will always contain exactly the same content.

3. Fetch the UTA Docker image from Docker Hub:

   $ docker pull biocommons/uta:$uta_v
   

   This process will likely take 1-3 minutes.

4. Run the image:

   $ docker run \
      -d \
      -e POSTGRES_PASSWORD=some-password-that-you-make-up \
      -v /tmp:/tmp \
      -v uta_vol:/var/lib/postgresql/data \
      --name $uta_v \
      --network=host \
      biocommons/uta:$uta_v
   

   The first time you run this image, it will initialize a PostgreSQL database cluster, then download a database dump from biocommons and install it.

   -d starts the container in daemon (background) mode. To see progress:

   $ docker logs -f $uta_v
   

   You will see messages from several processes running in parallel. Near the end, you'll see:

   == You may now connect to uta.  No password is required.
   ...
   2020-05-28 22:08:45.654 UTC [1] LOG:  database system is ready to accept connections
   

   Hit Ctrl-C to stop watching logs. The container will still be running.

5. Test your installation

   With the test commands below, you should see a table dump with at least 4 lines showing schema_version, create date, license, and uta (code) version used to build the instance.

   $ psql -h localhost -U anonymous -d uta -c "select * from $uta_v.meta"
   
         key       |                               value
   ----------------+--------------------------------------------------------------------
    schema_version | 1.1
    created on     | 2015-08-21T10:53:50.666152
    license        | CC-BY-SA (http://creativecommons.org/licenses/by-sa/4.0/deed.en_US
    uta version    | 0.2.0a2.dev11+n52ed6e969cfc
    (4 rows)
   

6. (Optional) To configure hgvs to use this local installation, consult the hgvs documentation

Installing from database dumps

Users should prefer the public UTA instance (uta.biocommons.org) or the Docker installation wherever possible. When those options are not available, users may wish to create a local PostgreSQL database from database dumps. Users choosing this method of installation should be experienced with PostgreSQL administration.

The public site and Docker images are built from exactly the same dumps as provided below. Building a database from these should result in a local database that is essentially identical to those options.

Due to the heterogeneity of operating systems and PostgreSQL installations, installing from database dumps is unsupported.

The following commands will likely need modification appropriate for the installation environment.

1. Download an appropriate database dump from dl.biocommons.org.

2. Create a user and database.

   You may choose any username and database name you like. uta and uta_admin are likely to ease installation.

   $ createuser -U postgres uta_admin
   $ createuser -U postgres anonymous
   $ createdb -U postgres -O uta_admin uta
   

3. Restore the database.

   $ uta_v=uta_20210129b
   $ gzip -cdq $uta_v.pgd.gz | psql -U uta_admin -1 -v ON_ERROR_STOP=1 -d uta -Eae
   

Developer Setup

Virtual Environment

To develop UTA, follow these steps.

1. Set up a virtual environment using your preferred method. For example:

   $ python3 -m venv uta-venv
   $ source uta-venv/bin/activate
   

2. Clone UTA and install:

   $ git clone [email protected]:biocommons/uta.git
   $ cd uta
   $ pip install -e .[test]
   

3. Restore a database or load a new one using the instructions above.

4. To run the tests:

   $ python3 -m unittest
   

Docker

1. Clone UTA and build docker image:

    $ git clone [email protected]:biocommons/uta.git
    $ cd uta
    $ docker build -t uta .
   

2. Restore a database or load a new one using the instructions above.

3. Run container and tests

    $ docker run -it --rm uta bash
   

4. Testing

    $ docker build --target uta-test -t uta-test .
    $ docker run --rm uta-test python -m unittest
   

UTA update procedure

Requires docker.

0. Setup

Make directories:

mkdir -p $(pwd)/ncbi-data
mkdir -p $(pwd)/output/artifacts
mkdir -p $(pwd)/output/logs

Set variables:

export UTA_ETL_OLD_UTA_IMAGE_TAG=uta_20210129b
export UTA_ETL_OLD_UTA_VERSION=UTA_ETL_OLD_UTA_IMAGE_TAG
export UTA_ETL_NEW_UTA_VERSION=uta_20240512
export UTA_ETL_NCBI_DIR=./ncbi-data
export UTA_ETL_WORK_DIR=./output/artifacts
export UTA_ETL_LOG_DIR=./output/logs

Build the UTA image:

docker build --target uta -t uta-update .

1. Download SeqRepo data

docker compose run seqrepo-pull

Note: pulling data takes ~30 minutes and requires ~13 GB. Note: a container called seqrepo will be left behind.

2. Extract and transform data from NCBI

Download files from NCBI, extract into intermediate files, and load into UTA and SeqRepo.

See 2A for nuclear transcripts and 2B for mitochondrial transcripts.

2A. Nuclear transcripts

docker compose run ncbi-download
docker compose run uta-extract
docker compose run seqrepo-load
docker compose run uta-load

2B. Mitochondrial transcripts

docker compose -f docker-compose.yml -f misc/mito-transcripts/docker-compose-mito-extract.yml run mito-extract
docker compose run seqrepo-load
docker compose run uta-load

2C. Manual splign transcripts

To load splign-manual transcripts, the workflow expects an input txdata.yaml file and splign alignments. Define this path using the environment variable $UTA_SPLIGN_MANUAL_DIR. These file paths should exist:

• $UTA_SPLIGN_MANUAL_DIR/splign-manual/txdata.yaml
• $UTA_SPLIGN_MANUAL_DIR/splign-manual/alignments/*.splign

txdata.yaml defines the transcripts and their metadata. The alignments dir contains the splign alignments. To run the workflow:

export UTA_SPLIGN_MANUAL_DIR=$(pwd)/loading/data/splign-manual/
docker compose run splign-manual

UTA has updated and the database has been dumped into a pgd file in UTA_ETL_WORK_DIR. SeqRepo has been updated in place.

Migrations

UTA uses alembic to manage database migrations. To auto-generate a migration:

alembic -c etc/alembic.ini revision --autogenerate -m "description of the migration"

This will create a migration script in the alembic/versions directory. Adjust the upgrade and downgrade function definitions. To apply the migration:

alembic -c etc/alembic.ini upgrade head

To reverse a migration, use downgrade with the number of steps to reverse. For example, to reverse the last:

alembic -c etc/alembic.ini downgrade -1