Skip to content

Infer copy number variation (CNV) from scRNA-seq data. Plays nicely with Scanpy.

License

Notifications You must be signed in to change notification settings

BoevaLab/infercnvpy

 
 

Repository files navigation

infercnvpy: Scanpy plugin to infer copy number variation (CNV) from single-cell transcriptomics data

Tests Documentation PyPI

Infercnv is a scalable python library to infer copy number variation (CNV) events from single cell transcriptomics data. It is heavliy inspired by InferCNV, but plays nicely with scanpy and is much more scalable.

The main result of infercnv

WARNING:

This package is still experimental. The results have not been validated, except in that they look similar, but not identical, to the results of InferCNV.

We are happy about feedback and welcome contributions!

Getting started

Please refer to the documentation. In particular, the

Installation

You need to have Python 3.8 or newer installed on your system. If you don't have Python installed, we recommend installing Mambaforge.

There are several alternative options to install infercnvpy:

  1. Install the latest release of infercnvpy from PyPI <https://pypi.org/project/infercnvpy/>_:
pip install infercnvpy
  1. Install the latest development version:
pip install git+https://github.com/icbi-lab/infercnvpy.git@main

To (optionally) run the copyKAT algorithm, you need a working R installation and the copykat package installed. Usually, if R is in your PATH, rpy2 automatically detects your R installation. If you get an error message while importing infercnvpy, try setting the R_HOME environment variable before importing infercnvpy:

import os

os.environ["R_HOME"] = "/usr/lib/R"
import infercnvpy

Release notes

See the changelog.

Contact

For questions and help requests, you can reach out in the scverse discourse. If you found a bug, please use the issue tracker.

Citation

n/a

About

Infer copy number variation (CNV) from scRNA-seq data. Plays nicely with Scanpy.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%