Performs Slingshot trajectory inference — perform.slingshot.trajectory • IBRAP

Generates slingshot trajectory inference on the defined reduction and clustering

perform.slingshot.trajectory(
  object,
  reduction,
  assay,
  clust.method,
  column,
  start.clus = NULL,
  end.clus = NULL,
  verbose = FALSE,
  seed = 1234,
  ...
)

Arguments

object: IBRAP S4 class object
reduction: Character. String defining which reduction to supply to the clustering algorithm. Default = NULL
assay: Character. String containing indicating which assay to use
clust.method: Character. Which cluster method should be used utilised from clustering results, if `'metadata'` is supplied, you will access the metadata.
column: Character. Which column within the isolated clust.method should be used to define cell type annoation.
start.clus: Character. Which cluster should start the trajectory, if NULL then slingshot will attempt to discover this. Default = NULL
end.clus: Character. Which cluster should end the trajectory, if NULL then slingshot will attempt to discover this. Default = NULL
verbose: Logical Should function messages be printed?
seed: Numeric. What should the seed be set as. Default = 1234
...: arguments to be passed to slingshot::slingshot

Value

A SingleshotDataSet class results object containing cellular lineages/curves

Examples


traj_res <- perform.slingshot.trajectory(object = object, reduction = 'pca_umap', 
                                         assay = 'SCT', clust.method = 'metadata', 
                                         column = 'celltype')
#> Error in is(object, "IBRAP"): object 'object' not found
                                         
plot.slingshot(result = traj_red, object = traj, assay = 'SCT', relevant = F, Pseudotime = T)
#> Error in is(object = result$assignments, "SlingshotDataSet"): object 'traj_red' not found