multimodal-cci 1.2.0

A Python package for processing multi-modal CCI data

MMCCI: Multimodal Cell-Cell Interaction Integrative Analysis of Single Cell and Spatial Data

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Paper
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MMCCI is a fast and lightweight Python package for integrating and visualizing CCI networks within and between multiple modalities at the level of the individual LR pair. It works on scRNA-seq and spatial transcriptomics data samples that have been processed through the following CCI algorithms:

1. stLearn
2. CellChat
3. CellPhoneDB
4. NATMI
5. Squidpy

Getting Started

Installation

MMCCI can be installed with pip

pip install multimodal-cci

Documentation

Documentation and Tutorials are available here and we are commited to maintaining the software and addressing issues raised by users.

• There is a brain aging tutorial notebook here
• There is a melanoma tutorial notebook here
• To understand how to load CCI results from different tools, look at this notebook here

CCI Integration

MMCCI allows users to integrate multiple CCI results together, both:

1. Samples from a single modality (eg. Visium)
2. Samples from multiple modalities (eg. Visium, Xenium and CosMX)

CCI Analysis

MMCCI provides multiple useful analyses that can be run on the integrated networks or from a single sample:

1. Network comparison between groups with permutation testing
2. CLustering of LR pairs with similar networks
3. Clustering of spots/cells with similar interaction scores
4. Sender-receiver LR querying
5. GSEA pathway analysis

Pipeline Diagram

Citing MMCCI

If you have used MMCCI in your research, please consider citing us:

Hockey, L., Mulay, O., Xiong, Z., Khosrotehrani, K., Nefzger, C. M., & Nguyen, Q. (2024). MMCCI: Multimodal Cell-Cell Interaction Integrative Analysis of Single Cell and Spatial Data. bioRxiv. doi:10.1101/2024.02.28.582639

BSD License

Copyright (c) 2024, Genomics and Machine Learning lab All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

• Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

• Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

• Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.