Skip to main content

benchmarking gene regulatory networks

Project description

bengrn

codecov CI PyPI version Documentation Status Downloads Downloads Downloads GitHub issues Code style: black DOI

Benchmark your gene regulatory networks inference algorithm (from scRNAseq or bulk RNAseq dataset) with BenGRN

The package is supposed to work with GRnnData and only uses biological ground truth datasets.

It can run Genie3 & pyscenic on your data as a comparison

It has 3 main different types of key ground truth data to compare your GRN to:

  • Mc Calla et al.'s ChIP+Perturb ground truth
  • omnipath's literature curated ground truth
  • genome wide perturb seq 's dataset

You can find the documentation here

Install it from PyPI

pip install bengrn

Install it locally and run the notebooks:

git clone https://github.com/jkobject/benGRN.git
pip install -e benGRN

Usage

from bengrn import BenGRN
from bengrn import some_test_function

# a GRN in grnndata formart
grndata

BenGRN(grndata).do_tests()
#or
some_test_function(grndata)

see the notebooks in docs:

  1. omnipath
  2. genome wide perturb seq
  3. Mc Calla

Development

Read the CONTRIBUTING.md file.

Awesome Benchmark of Gene Regulatory Networks created by @jkobject

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

bengrn-1.0.2.tar.gz (52.3 kB view details)

Uploaded Source

Built Distribution

bengrn-1.0.2-py3-none-any.whl (56.9 kB view details)

Uploaded Python 3

File details

Details for the file bengrn-1.0.2.tar.gz.

File metadata

  • Download URL: bengrn-1.0.2.tar.gz
  • Upload date:
  • Size: 52.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.6.1 CPython/3.11.4 Linux/5.15.0-107-generic

File hashes

Hashes for bengrn-1.0.2.tar.gz
Algorithm Hash digest
SHA256 7c643f1ed5d47b79508e338d7b146719b90ef13ce50ede11c7a8d38aaadb92bd
MD5 733288b42f51ebefe3f6b1ae2253063c
BLAKE2b-256 35ef948a971b7cb3eb94c66644a511a888220e2a8a4d6a8bf147ae65ac8e224f

See more details on using hashes here.

File details

Details for the file bengrn-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: bengrn-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 56.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.6.1 CPython/3.11.4 Linux/5.15.0-107-generic

File hashes

Hashes for bengrn-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 fb50202b40c4410d3c61d2d99e97298f813e7f18810c71b77ba65f1670e8e730
MD5 6ac9f4d446cf018419732c25308bccad
BLAKE2b-256 968a7934634407dbb13d7af6626775f1d06742dbbcfe1876447fb35a8eb58904

See more details on using hashes here.

Supported by

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