Singlecell Interpretable Tensor Decomposition (scITD) employs the Tucker tensor decomposition to extract multicelltype gene expression patterns that vary across donors/individuals. This tool is geared for use with singlecell RNAsequencing datasets consisting of many source donors. The method has a wide range of potential applications, including the study of interindividual variation at the populationlevel, patient subgrouping/stratification, and the analysis of samplelevel batch effects. Each "multicellular process" that is extracted consists of (A) a multi cell type gene loadings matrix and (B) a corresponding donor scores vector indicating the level at which the corresponding loadings matrix is expressed in each donor. Additional methods are implemented to aid in selecting an appropriate number of factors and to evaluate stability of the decomposition. Additional tools are provided for downstream analysis, including integration of gene set enrichment analysis and ligandreceptor analysis. Tucker, L.R. (1966) <doi:10.1007/BF02289464>. Unkel, S., Hannachi, A., Trendafilov, N. T., & Jolliffe, I. T. (2011) <doi:10.1007/s1325301100559>. Zhou, G., & Cichocki, A. (2012) <doi:10.2478/v1017501200514>.
Package details 


Author  Jonathan Mitchel [cre, aut], Evan Biederstedt [aut], Peter Kharchenko [aut] 
Maintainer  Jonathan Mitchel <jonathan.mitchel3@gmail.com> 
License  GPL3 
Version  1.0.0 
Package repository  View on CRAN 
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