scConnect : a method for exploratory analysis of cell–cell communication based on single-cell RNA-sequencing data
| Autor: | Ola Spjuth, Malin C. Lagerström, Jon E. T. Jakobsson |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Cell signaling Cell type AcademicSubjects/SCI01060 Computer science In silico Cell Gene Expression Computational biology Biochemistry 03 medical and health sciences 0302 clinical medicine medicine Molecular Biology 030304 developmental biology computer.programming_language 0303 health sciences Neurosciences Python (programming language) Original Papers Pipeline (software) Computer Science Applications Multicellular organism Computational Mathematics medicine.anatomical_structure Single cell sequencing Computational Theory and Mathematics 030220 oncology & carcinogenesis computer Neurovetenskaper |
| Zdroj: | Bioinformatics |
| Popis: | Motivation Cell to cell communication is critical for all multicellular organisms, and single-cell sequencing facilitates the construction of full connectivity graphs between cell types in tissues. Such complex data structures demand novel analysis methods and tools for exploratory analysis. Results We propose a method to predict the putative ligand–receptor interactions between cell types from single-cell RNA-sequencing data. This is achieved by inferring and incorporating interactions in a multi-directional graph, thereby enabling contextual exploratory analysis. We demonstrate that our approach can detect common and specific interactions between cell types in mouse brain and human tumors, and that these interactions fit with expected outcomes. These interactions also include predictions made with molecular ligands integrating information from several types of genes necessary for ligand production and transport. Our implementation is general and can be appended to any transcriptome analysis pipeline to provide unbiased hypothesis generation regarding ligand to receptor interactions between cell populations or for network analysis in silico. Availability and implementation scConnect is open source and available as a Python package at https://github.com/JonETJakobsson/scConnect. scConnect is directly compatible with Scanpy scRNA-sequencing pipelines. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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