dbdimitrov / cell2cell

User-friendly tool to infer cell-cell interactions and communication from gene expression of interacting proteins

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Inferring cell-cell interactions from transcriptomes with cell2cell

PyPI Version Downloads

Getting started

Please refer to the cell2cell website, which includes tutorials and documentation

Installation

First, install Anaconda following this tutorial

Once installed, create a new conda environment:

conda create -n cell2cell -y python=3.7 jupyter

Activate that environment:

conda activate cell2cell

Then, install cell2cell:

pip install cell2cell

Examples


plot

  • A toy example using the under-the-hood methods of cell2cell is available here. This case allows personalizing the analyses in a higher level, but it may result harder to use.
  • A toy example using an Interaction Pipeline for bulk data is available here. An Interaction Pipeline makes cell2cell easier to use.
  • A toy example using an Interaction Pipeline for single-cell data is available here. An Interaction Pipeline makes cell2cell easier to use.
  • An example of using cell2cell to infer cell-cell interactions across the whole body of C. elegans is available here

plot


Common issues

  • When running Tensor-cell2cell (InteractionTensor.compute_tensor_factorization() or InteractionTensor.elbow_rank_selection()), a common error is associated with Memory. This may happen when the tensor is big enough to make the computer run out of memory when the input of the functions in the parentheses is init='svd'. To avoid this issue, just replace it by init='random'.

Ligand-Receptor pairs

  • A repository with previously published lists of ligand-receptor pairs is available here. You can use any of these lists as an input of cell2cell.

Citation

About

User-friendly tool to infer cell-cell interactions and communication from gene expression of interacting proteins

License:BSD 3-Clause "New" or "Revised" License


Languages

Language:Python 100.0%