bin_scdata: Bin genes by mean expression.

In scFeatureFilter: A correlation-based method for quality filtering of single-cell RNAseq data

Description

Divides the genes that were not included in the top window in windows of the same size with decreasing mean expression levels.

Usage

bin_scdata(dataset, window_number = NULL, window_size = NULL,
  verbose = TRUE)

Arguments

dataset	A list, containing the top window generated by extract_top_genes as the first element, and the rest of undivided genes as the second. Usually the output of define_top_genes
window_number	An integer, indicating the number of bins to be used.
window_size	An integer, indicating the number of genes to be included in each window. Ignored if window_size is defined.
verbose	A boolean. Should the function print a message about window size or the number of windows created?

Details

Two binning methods are available:

• window_number: Divides the genes into the number of windows specified.

• window_size: Divides the genes into windows of the size specified.

This function adds a bin number column to the data frame.

This function is designed to take the list output by the extract_top_window function as an argument, operating only on the second element of it. Once the genes in it have been binned, both elements of the list are bound together in a data frame and returned. The output contains a new column bin, which indicates the window number assigned to each gene.

Value

A data frame containing the binned genes.

Examples

library(magrittr)
expMat <- matrix(
    c(1, 1, 1,
      1, 2, 3,
      0, 1, 2,
      0, 0, 2),
    ncol = 3, byrow = TRUE, dimnames = list(paste("gene", 1:4), paste("cell", 1:3))
)

calculate_cvs(expMat) %>%
    define_top_genes(window_size = 1) %>%
    bin_scdata(window_number = 2)

calculate_cvs(expMat) %>%
    define_top_genes(window_size = 1) %>%
    bin_scdata(window_size = 1)

scFeatureFilter documentation built on Nov. 8, 2020, 7:49 p.m.