predict.SlingshotDataSet: Predict from a Slingshot model
In slingshot: Tools for ordering single-cell sequencing

Description Usage Arguments Details Value See Also Examples

Map new observations onto simultaneous principal curves fitted by slingshot.

1 2	## S4 method for signature 'SlingshotDataSet' predict(object, newdata = NULL)

`object`	a `SlingshotDataSet` containing simultaneous principal curves to use for prediction.
`newdata`	a matrix or data frame of new points in the same reduced-dimensional space as the original input to `slingshot` (or `getLineages`).

This function is a method for the generic function predict with signature(object = "SlingshotDataSet"). If no newdata argument is provided, it will return the original results, given by object.

A SlingshotDataSet object based on the input newdata. New cells are treated as "unclustered" and the lineages and adjacency slots are intentionally left blank, to distinguish these results from the original slingshot output. The curves slot represents the projections of each new cell onto the existing curves. As with standard slingshot output, the lineage-specific pseudotimes and assignment weights can be accessed via the functions slingPseudotime and slingCurveWeights.

slingshot, SlingshotDataSet

data("slingshotExample")
rd <- slingshotExample$rd
cl <- slingshotExample$cl
sds <- slingshot(rd, cl, start.clus = '1')

x <- cbind(runif(100, min = -5, max = 10), runif(100, min = -4, max = 4))
predict(sds, x)