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We here present SIMLR (Single-cell Interpretation via Multi-kernel LeaRning),an open-source tool that implements a novel framework to learn asample-to-sample similarity measure from expression data observed forheterogenous samples. SIMLR can be effectively used to perform tasks such asdimension reduction, clustering, and visualization of heterogeneous populationsof samples. SIMLR was benchmarked against state-of-the-art methods for thesethree tasks on several public datasets, showing it to be scalable and capableof greatly improving clustering performance, as well as providing valuableinsights by making the data more interpretable via better a visualization.Availability and Implementation  SIMLR is available on GitHub in both R and MATLAB implementations.Furthermore, it is also available as an R package on http://bioconductor.org.

SIMLR: A Tool for Large‐Scale Genomic Analyses by Multi‐Kernel Learning