Skip to main content

TFit : Assessing the combinatorial potential of Transcription Factors in Gene Regulation

Project description

TFitPy (Transcription Factor Fitness)

TFitPy (which stands for Transcription Factor Fitness) is a python package to access the combinatorial potential of Transcription Factors in Gene Regulation of a target gene.

Installation

Use poetry add tfitpy@^0.0.6 --python ">=3.11,<3.14.1 || >3.14.1,<4.0" if facing version issues

Or using PIP: pip install tfitpy

Initial setup

This package requires a lot of biological data to compute various validation indices.

Validate Co-regulators of a target gene

Step 1 : Load datasets

Step 2 : Generate indices

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

tfitpy-0.9.10.tar.gz (46.1 kB view details)

Uploaded Source

Built Distribution

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

tfitpy-0.9.10-py3-none-any.whl (55.9 kB view details)

Uploaded Python 3

File details

Details for the file tfitpy-0.9.10.tar.gz.

File metadata

  • Download URL: tfitpy-0.9.10.tar.gz
  • Upload date:
  • Size: 46.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for tfitpy-0.9.10.tar.gz
Algorithm Hash digest
SHA256 a2d4b96c54c95191365d402033303935ba676b758865b63ee84aed73cc81cf77
MD5 a524a4ec5cf02ecfdbb3638fa996b256
BLAKE2b-256 839235f6fc0bf9ae59987a1b3a0a1b30d31c66fcfc003aeebb418ef3b7152696

See more details on using hashes here.

Provenance

The following attestation bundles were made for tfitpy-0.9.10.tar.gz:

Publisher: package.yaml on shubhvjain/tfit

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file tfitpy-0.9.10-py3-none-any.whl.

File metadata

  • Download URL: tfitpy-0.9.10-py3-none-any.whl
  • Upload date:
  • Size: 55.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for tfitpy-0.9.10-py3-none-any.whl
Algorithm Hash digest
SHA256 b8b5511df6f93449e3df58c8abf0d13233e9522dd10e7a6126c1b2889b25453b
MD5 52c51e1b7096cddbe84c0566b9eb48fb
BLAKE2b-256 d7e8c80a9174976a1b1046e35c01bd9d364dc0344aec7cff100f10305f711845

See more details on using hashes here.

Provenance

The following attestation bundles were made for tfitpy-0.9.10-py3-none-any.whl:

Publisher: package.yaml on shubhvjain/tfit

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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