Simulate counts from cluster in two conditions using the SparseDC method.
SparseDCParams object containing simulation parameters.
logical. Whether to print progress messages
any additional parameter settings to override what is provided in
This function is just a wrapper around
sim_data that takes a
SparseDCParams, runs the simulation then converts the
output from log-expression to counts and returns a
SingleCellExperiment object. The original
simulated log-expression values are returned in the
sim_data and the SparseDC paper for
more details about how the simulation works.
SingleCellExperiment containing simulated counts
Campbell K, Yau C. Uncovering genomic trajectories with heterogeneous genetic and environmental backgrounds across single-cells and populations. bioRxiv (2017).
Barron M, Zhang S, Li J. A sparse differential clustering algorithm for tracing cell type changes via single-cell RNA-sequencing data. Nucleic Acids Research (2017).
sim <- sparseDCSimulate()
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