Skip to main content

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.

Project description

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 3.10 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-hypernode.com/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

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

infercnvpy-0.5.0.tar.gz (8.5 MB view details)

Uploaded Source

Built Distribution

infercnvpy-0.5.0-py3-none-any.whl (3.8 MB view details)

Uploaded Python 3

File details

Details for the file infercnvpy-0.5.0.tar.gz.

File metadata

  • Download URL: infercnvpy-0.5.0.tar.gz
  • Upload date:
  • Size: 8.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for infercnvpy-0.5.0.tar.gz
Algorithm Hash digest
SHA256 15c492a4f22db0ccb1055b4b0af1fadd0aa93ca73ac377853ad6bf5c4eb4982d
MD5 288ed35678d8d709aeb6d192f7e6304d
BLAKE2b-256 34ee4a3652d7a329115e355efd3b347e5213c3db3cb30bc46d52a6f0fe07a76c

See more details on using hashes here.

Provenance

File details

Details for the file infercnvpy-0.5.0-py3-none-any.whl.

File metadata

  • Download URL: infercnvpy-0.5.0-py3-none-any.whl
  • Upload date:
  • Size: 3.8 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for infercnvpy-0.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0677a0777a6a0bd45168cc5c848d4c2f42037e7a015f93d022df4aafde69f77c
MD5 4f5b94a41fd7c53e326db5f16af2dca3
BLAKE2b-256 f2f37bcf346e9321a499c3791f73238dde34f26b2c1dccfdf1bb7c43c0c46603

See more details on using hashes here.

Provenance

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