Installation

We recommend working with environments such as Conda or virtualenv, so that python and R dependencies are in one place. Please also check out scib-pipeline for ready-to-use environments and an end-to-end workflow.

Requirements

  • Linux or UNIX system

  • Python >= 3.7

  • R >= 3.6

Installation with pip

The scib python package is available on PyPI and can be installed through

pip install scib

Alternatively, you can also install the package directly from GitHub directly via

pip install git+https://github.com/theislab/scib.git

Additionally, in order to run the R package kBET, you need to install it through R.

install.packages('remotes')
remotes::install_github('theislab/kBET')

Note

By default dependencies for integration methods are not installed due to dependency clashes. In order to use integration methods, see

Installing additional packages

This package contains code for running integration methods as well as for evaluating their output. However, due to dependency clashes, scib is only installed with the packages needed for the metrics. In order to use the integration wrapper functions, we recommend to work with different environments for different methods, each with their own installation of scib. You can install optional Python dependencies via pip as follows:

pip install scib[bbknn]  # using BBKNN
pip install scib[scanorama]  # using Scanorama
pip install scib[bbknn,scanorama]  # Multiple methods in one go

Note

Zsh often doesn’t like square brackets. If you are a zsh user, use quotation marks around any statements containing square brackets. For example:

pip install 'scib[bbknn]'

The setup.cfg of the source code for a full list of Python dependencies.