cnaCor: Cell - Tumour CNA Correlations

In jlaffy/infercna: Infer Copy Number Alterations And Clonality In (Single-Cell) RNA-seq Data

Cell - Tumour CNA Correlations

Description

Compute the pairwise correlations between individual cells' CNA values and the average CNA values in their tumour of origin.

Usage

cnaCor(
  cna,
  cor.method = "pearson",
  cell.quantile = NULL,
  gene.quantile.for.cells = NULL,
  gene.quantile = NULL,
  cell.quantile.for.genes = NULL,
  refCells = NULL,
  samples = NULL,
  ...
)

Arguments

cna	a matrix of gene rows by cell columns containing CNA values.
cor.method	character string indicating the method to use for the pairwise correlations. E.g. 'pearson', 'spearman'. Default: 'pearson'
gene.quantile	calculate CNA measures including only top / "hotspot" genes according to their squared CNA values across all cells. Value between 0 and 1 denoting the quantile of genes to include. Default: NULL
refCells	a character vector of cell ids to exclude from average CNA profile that each cell is correlated to. You can pass reference normal cell ids to this argument if these are known. Default: NULL
samples	if CNA correlations should be calculated within cell subgroups, provide i) a list of cell id groups, ii) a character vector of sample names to group cells by, iii) TRUE to extract sample names from cell ids and subsequently group. Default: NULL
...	other arguments passed to scalop::unique_sample_names if samples = TRUE.

Value

a numeric vector or list of numeric vectors

jlaffy/infercna documentation built on Jan. 26, 2024, 11:24 p.m.