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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.
The new version of DIALOGUE is now available! New features include the unsupervised, data-driven identification of the cell types participating in each program, and permutation tests to identify generalizable MCPs.
To install DIALOGUE you can either use devtools::install_github("DIALOGUE",username) or just download its R package and use devtools::install("DIALOGUE")
The input consists of single-cell transcriptomes of different cell types, usually together with a more compact representation (e.g., PCs). The output will be multicellular programs (MCPs) of co-regulated genes across the different cell types, their expression across the cells, and association with specific phenotype(s) of interest. Each MCP consists of multiple cell-type-specific gene subsets.
See the tutorial for more details.
- R (tested in R version 3.4.0).
- R libraries: lme4, lmerTest, PMA, plyr, matrixStats, psych, stringi, RColorBrewer, unikn, reshape2, ggplot2, grid, beanplot, ppcor, Hmisc