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 3.8 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

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-0.4.0.tar.gz (50.5 MB view details)

Uploaded Source

Built Distribution

infercnvpy-0.4.0-py3-none-any.whl (3.8 MB view details)

Uploaded Python 3

File details

Details for the file infercnvpy-0.4.0.tar.gz.

File metadata

  • Download URL: infercnvpy-0.4.0.tar.gz
  • Upload date:
  • Size: 50.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.6

File hashes

Hashes for infercnvpy-0.4.0.tar.gz
Algorithm Hash digest
SHA256 00b8d78726db0a70bdb4d887fd503a484873244a60b9f58a0979aa75ba6e48cb
MD5 4f336d3f2f1f21c63492346a8d355164
BLAKE2b-256 df56561aa401794b03e181d8c38948b41c969ce1f5a068ea071696ea9734b563

See more details on using hashes here.

File details

Details for the file infercnvpy-0.4.0-py3-none-any.whl.

File metadata

  • Download URL: infercnvpy-0.4.0-py3-none-any.whl
  • Upload date:
  • Size: 3.8 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.6

File hashes

Hashes for infercnvpy-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e6f92bf76ca0ef97b7520637faf73b4f98d835ae3c16077291999456f11969b9
MD5 41c3f8e14ded0096177e36edc1b84528
BLAKE2b-256 aee2cc77e389636f394968a7fa72dcbb4f77c3ed91a2751ade23ee9321095561

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