entropy: entropy

Description Usage Arguments Details Value Examples

View source: R/otherMetrics.R

Description

entropy

Usage

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entropy(
  sce,
  group,
  k,
  dim_red = "PCA",
  assay_name = "logcounts",
  n_dim = 10,
  res_name = NULL
)

Arguments

sce

SingleCellExperiment object, with the integrated data.

group

Character. Name of group/batch variable. Needs to be one of names(colData(sce)).

k

Numeric. Number of k-nearest neighbours (knn) to use.

dim_red

Character. Name of embeddings to use as subspace for distance distributions. Default is "PCA".

assay_name

Character. Name of the assay to use for PCA. Only relevant if no existing 'dim_red' is provided. Must be one of names(assays(sce)). Default is "logcounts".

n_dim

Numeric. Number of dimensions to include to define the subspace.

res_name

Character. Appendix of the result score's name (e.g. method used to combine batches).

Details

The entropy function calculates the Shannon entropy of the group variable within each cell's k-nearest neighbourhood. For balanced batches a Shannon entropy close to 1 indicates high randomness and mixing. For unbalanced batches entropy should be interpreted with caution, but could work as a relative measure in a comparative setting.

Value

A SingleCellExperiment with the entropy score within colData.

Examples

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library(SingleCellExperiment)
sim_list <- readRDS(system.file("extdata/sim50.rds", package = "CellMixS"))
sce <- sim_list[[1]][, c(1:15, 400:420, 16:30)]

sce <- entropy(sce, "batch", k = 20)

almutlue/CellMixS documentation built on Dec. 22, 2020, 11:07 a.m.