Cell pseudotime reconstruction based on genetic algorithm
The package pseudoga can be used to perform pseudotime analysis on single cell gene expression data. Given a homogeneous population of cells, the cells can be ordered to form a trajectory. Given a heterogeneous population and cell cluster ids, the packages can be used to find a tree structure based on pseudotime ordering of cells.
Input must be provided as SingleCellExperiment object with the expression matrix denoting rows as genes and columns as cells.
library(pseudoga)
library(SingleCellExperiment)
counts <- matrix(rpois(10000, lambda = 10), ncol=100, nrow=100)
sce <- SingleCellExperiment(list(counts=counts))
sce<-pseudoga(sce) #Usual PseudoGA
sce1<-pseudoga_parallel(sce) #PseudoGA based on subsampling
The object "Pseudotime" under "colData" contains inferred pseduotime by PseudoGA.
For large number of cells, "pseudoga_parallel" is more suitable. One should check all the parameters carefully before applying these two functions. For details about the parameters, type:
?pseudoga
?pseudoga_parallel