Skip to main content

Automatic DCR: a modified version of Decombinator for uncommon specific TCR annotation-related tasks

Project description

autoDCR

Jamie Heather, MGH, 2025

PyPI - Version License: MIT Static Badge

autoDCR (short for automatic Decombinator) is a python script to perform T cell receptor (TCR) gene annotation. This is inspired by and in part built upon the core functionality of Decombinator, the TCR analysis software developed by the Chain lab at UCL. It uses a similar conceptual framework of using fast Aho-Corasick tries to search for the presence of 'tag' sequences in DNA reads, and use these to identify V and J TCR genes. However it applies that core concept in different ways, to perform several niche functions that are not well catered to in other TCR annotation pipelines.

Note that autoDCR is under development and should be considered experimental, specifically aiming to cater to specific case uses. The documentation can be found here: https://jamieheather.github.io/autoDCR/.

The 0.2.7 version used in prior publications can be accessed via the releases page.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

autodcr-0.3.0.tar.gz (31.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

autodcr-0.3.0-py3-none-any.whl (36.0 kB view details)

Uploaded Python 3

File details

Details for the file autodcr-0.3.0.tar.gz.

File metadata

  • Download URL: autodcr-0.3.0.tar.gz
  • Upload date:
  • Size: 31.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.2 CPython/3.12.0 Darwin/24.5.0

File hashes

Hashes for autodcr-0.3.0.tar.gz
Algorithm Hash digest
SHA256 805491d34c205860d7e4ded391ef0f84c68a44d55709cbbb60e6509345b247e4
MD5 a162fb46327212f42c251c5effc194ae
BLAKE2b-256 3da57ad8e5e300994d3f4bd875a26009d44519035703cf21776f2c12fdfb3eba

See more details on using hashes here.

File details

Details for the file autodcr-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: autodcr-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 36.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.2 CPython/3.12.0 Darwin/24.5.0

File hashes

Hashes for autodcr-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 709a3681fe5b01cc0b96f133dd2968ef49b728fddafdd0a68821590d910fffd9
MD5 382a64f2e93d7ccc027b6d41be0e5ca3
BLAKE2b-256 cf035fd7d90f209788009411e77391ac23b5facc92151d43945b4c33a6e781ea

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page