trendSceek#

Last Updated: Oct 02, 2023

Description#

Compute spatial variable genes with trendsceek method

Usage#

trendSceek(
  gobject,
  feat_type = NULL,
  spat_unit = NULL,
  spat_loc_name = "raw",
  expression_values = c("normalized", "raw"),
  subset_genes = NULL,
  nrand = 100,
  ncores = 8,
  ...
)

Arguments#

`gobject`	Giotto object
`feat_type`	feature type
`spat_unit`	spatial unit
`spat_loc_name`	name for spatial locations
`expression_values`	gene expression values to use
`subset_genes`	subset of genes to run trendsceek on
`nrand`	An integer specifying the number of random resamplings of the mark distribution as to create the null-distribution.
`ncores`	An integer specifying the number of cores to be used by BiocParallel
`...`	Additional parameters to the `trendsceek_test` function

Details#

This function is a wrapper for the trendsceek_test method implemented in the trendsceek package Publication: doi:10.1038/nmeth.4634

Value#

data.frame with trendsceek spatial genes results