preprocess_for_clonealign: Preprocess data for input to clonealign

In kieranrcampbell/clonealign: Assigning scRNA-seq to clone-of-origin using copy number from ultra-low-depth scDNA-seq

Description

Preprocess data for input to clonealign, filtering for cells and genes with minimum counts, along with removing outlying genes, and genes with the same copy number between clones.

Usage

preprocess_for_clonealign(
  gene_expression_data,
  copy_number_data,
  min_counts_per_gene = 20,
  min_counts_per_cell = 100,
  remove_outlying_genes = TRUE,
  nmads = 10,
  max_copy_number = 6,
  remove_genes_same_copy_number = TRUE
)

Arguments

gene_expression_data	Input gene expression data. See clonealign for details
copy_number_data	Input copy number data. See clonealign for details
min_counts_per_gene	Minimum counts per gene for the gene to pass filtering
min_counts_per_cell	Minimum counts per cell for the cell to pass filtering
remove_outlying_genes	Logical - should genes whose expression is an outlier wrt all others be removed?
nmads	The number of median absolute deviations (MADs) the per-gene mean of the raw counts is from the overall mean to be considered an outlier
max_copy_number	Maximum copy number per gene to retain (see "saturation" under original paper)
remove_genes_same_copy_number	Logical - should genes with the same copy number in all clones be removed?

Value

A list with entries gene_expression_data and copy_number_data for input to clonealign, along with names of the retained genes and cells after filtering.

Examples

library(SummarizedExperiment)
data("example_sce")
L <- rowData(example_sce)[,c("A", "B", "C")]
ca_data <- preprocess_for_clonealign(example_sce, L)

kieranrcampbell/clonealign documentation built on Dec. 18, 2020, 3:49 a.m.