Skip to main content

A framework for generating single-cell gene expression data

Project description


A framework for generating single-cell gene expression data

Release Notes

Installation

Both on Windows or Linux (CentOS, Ubuntu), just

pip install -r requirements.txt

Pyvips linux installation

# linux environ install pyvips using conda
conda install --channel conda-forge pyvips

Pyvips windows install vips from vips

pip install --user pyvips==2.2.1
# add vips path when running python script
import os
vipsbin = r'c:\vips-dev-8.13\bin'
os.environ['PATH'] = vipsbin + ';' + os.environ['PATH']

Develop mode

git clone https://gitlab.genomics.cn/biointelligence/implab/stero-rnd/cellbin/algorithms/cellbin.git
conda activate env # activate your env
python setup.py develop --no-deps  # develop mode, if you already have deps installed

Usage

contribute

We love your input! We want to make contributing to cellbin as easy and transparent as possible. Please see,

  • When you need to change other people's modules, remember to note the change information in the change location. like, a = 0 # parameter value to zero [by jack]

Thank you to all our contributors!

Contact

For cellbin bugs and feature requests please visit

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

cell_bin-1.2.8-py3-none-any.whl (165.4 kB view hashes)

Uploaded Python 3

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