correlations_to_densities: Transform the correlation table to density distributions of...

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

Description

Takes the output of correlate_windows and computes density curves of correlation coefficient for each window comparison.

Usage

correlations_to_densities(df, n = 64, absolute_cc = TRUE)

Arguments

df	A data frame, usually the output of correlate_windows.
n	Resolution of the correlation density curve. Default to 64.
absolute_cc	Should the function use the absolute value of correlation coefficients? Default to TRUE to simplify plots and avoid annoying, non-symmetrical, near 0, shifts of distributions.

Value

A tibble with columns bin, window, cor_coef and density.

Examples

library(magrittr)
expMat <- matrix(
    c(1, 1, 5,
      1, 2, 3,
      0, 1, 4,
      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 = 2) %>%
    bin_scdata(window_number = 1) %>%
    correlate_windows %>%
    correlations_to_densities

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