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DIALOGUE is a dimensionality reduction method that uses cross-cell-type associations to identify multicellular programs (MCPs) and map the cell transcriptome as a function of its environment. Given single-cell data, it combines penalized matrix decomposition with multilevel modeling to identify generalizable MCPs and examines their association with specific phenotypes of interest.
- R (tested in R version 3.4.0).
- R libraries: lme4, lmerTest, PMA, plyr, matrixStats, psych, stringi, RColorBrewer, unikn, reshape2, ggplot2
To install you can either use devtools::install_github("DIALOGUE",your_user_name) or just download tha package and use devtools::install("DIALOGUE")
Here you can find simple step-by-step examples on existing data and new data.
Single-cell transcriptomes of different cell types. Usually, the number of samples is much smaller than the number of genes in the data, and it is recommended to provide a more compact representation as input, for example, the first Principle Components (PCs).
Multicellular programs (MCPs) of co-regulated genes across the different cell types. Each MCP consists of cell-type-specific gene subsets. For more specific cell-cell "interactions" you can run the pairwise version - using the data of two cell types of interest as input. DIALOGUE can also identify MCPs that span more than two cell types (see Jerby-Arnon and Regev BioRxiv 2020 for examples on 5 and 6 cell types).
Jerby-Arnon and Regev Mapping multicellular programs from single-cell transcriptomes.