【slingshot】trajectory inference
condiments Paper • condimentsPaper
First example: TGF-beta dataset • bioc2021trajectories
slingshot requires a minimum of two inputs: (1)a matrix representing the cells in a reduced-dimensional space. (2)a vector of cluster labels.
主要步骤:
(1)getLineages function to identify global lineage structrue by construsting MST on the clusters
(2)getCurves function to construct smooth curves and infer the psudotime variable
- simulated dataset 1 (single trajectory) and dataset 2 (bifurcating)
#####dataset1
# generate synthetic count data representing a single lineage
means <- rbind(# non-DE genesmatrix(rep(rep(c(0.1,0.5,1,2,3), each = 300),100),ncol = 300, byrow = TRUE),# early deactivationmatrix(rep(exp(atan( ((300:1)-200)/50 )),50), ncol = 300, byrow = TRUE),# late deactivationmatrix(rep(exp(atan( ((300:1)-100)/50 )),50), ncol = 300, byrow = TRUE),# early activationmatrix(rep(exp(atan( ((1:300)-100)/50 )),50), ncol = 300, byrow = TRUE),# late activationmatrix(rep(exp(atan( ((1:300)-200)/50 )),50), ncol = 300, byrow = TRUE),# transientmatrix(rep(exp(atan( c((1:100)/33, rep(3,100), (100:1)/33) )),50), ncol = 300, byrow = TRUE)
)
counts <- apply(means,2,function(cell_means){total <- rnbinom(1, mu = 7500, size = 4)rmultinom(1, total, cell_means)
})
rownames(counts) <- paste0('G',1:750)
colnames(counts) <- paste0('c',1:300)
sce <- SingleCellExperiment(assays = List(counts = counts))#####dataset2
library(slingshot, quietly = FALSE)
data("slingshotExample")
rd <- slingshotExample$rd
cl <- slingshotExample$cldim(rd) # data representing cells in a reduced dimensional space
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