Calculate VISION scores — vision

Calculates an VISION-type scores for pathways based on DeTomaso, et al. Compared to other score types, you can also calculate delta-type scores between positive and negative gene indices, think epithelial vs mesenchymal gene signature, etc.

Usage

vision_sc(object, gs_list, streaming = NULL, .verbose = TRUE)

Arguments

object: SingleCells, MetaCells (or potentially other) class.
gs_list: Named nested list. Every element must itself be a list with at least a "pos" element holding the gene identifiers, and optionally a "neg" one. A bare character vector is not accepted. The gene identifiers need to be part of the variables of the object.
streaming: Optional Boolean. Shall the data be streamed in. Useful for larger data sets where you wish to avoid loading in the whole data. If NULL, will automatically detect. Ignored when applied to MetaCells.
.verbose: Boolean or integer. Controls verbosity and returns run times. FALSE -> quiet, TRUE or 1L -> normal verbosity, 2L -> detailed verbosity.

Value

The VISION scores in form of a matrix that is cells x gene sets or as ScMatrixRes pending the input.

References

DeTomaso, et al., Nat. Commun., 2019

Examples

# a signed signature alongside a plain one
sc <- demo_single_cells()
gs_list <- list(
  programme_a = list(
    pos = get_gene_names(sc)[1:10],
    neg = get_gene_names(sc)[11:20]
  ),
  programme_b = list(pos = get_gene_names(sc)[21:30])
)
res <- vision_sc(sc, gs_list = gs_list, .verbose = FALSE)
dim(res)
#> [1] 500   2

unlink(sc@dir_data, recursive = TRUE, force = TRUE)