Python library to infer copy number variation (CNV) from single-cell RNA-seq data
Project description
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.
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
Tutorial, and 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 Miniconda.
There are several alternative options to install infercnvpy:
Install the latest release of infercnvpy from PyPI:
pip install infercnvpy
Install the latest development version:
pip install git+https://github.com/icbi-lab/infercnvpy.git@master
Release notes
See the release section.
Contact
Please use the issue tracker.
Citation
n/a
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file infercnvpy-0.1.2.tar.gz
.
File metadata
- Download URL: infercnvpy-0.1.2.tar.gz
- Upload date:
- Size: 4.7 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.26.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | e2a92dff8e43fd95de79d0ca9a4eab89d3ed8be2570a5ab95624da6d1a145c55 |
|
MD5 | d6866498e6ff12cb0796daf5b8a00d8d |
|
BLAKE2b-256 | bdfb6ad178745eae2a5ca29935b054e33e947d2605fc81ba3a864bfc20461db4 |
File details
Details for the file infercnvpy-0.1.2-py3-none-any.whl
.
File metadata
- Download URL: infercnvpy-0.1.2-py3-none-any.whl
- Upload date:
- Size: 3.8 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.26.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c2c7a546e6a3a44675e984c55d07907025765fee33c07b925f3f6a8e291fb3cf |
|
MD5 | 629333f69d73de87b17273af22341f3e |
|
BLAKE2b-256 | 3be2964482ecd641039c164725ad99c6e4af58fb16e0cdcf0f0cdba98f6aa335 |