pair_corr: Pairwise scatter and correlation plot of counts

In federicomarini/pcaExplorer: Interactive Visualization of RNA-seq Data Using a Principal Components Approach

Pairwise scatter and correlation plot of counts

Description

Pairwise scatter and correlation plot of counts

Usage

pair_corr(df, log = FALSE, method = "pearson", use_subset = TRUE)

Arguments

df	A data frame, containing the (raw/normalized/transformed) counts
log	Logical, whether to convert the input values to log2 (with addition of a pseudocount). Defaults to FALSE.
method	Character string, one of pearson (default), kendall, or spearman as in cor
use_subset	Logical value. If TRUE, only 1000 values per sample will be used to speed up the plotting operations.

Value

A plot with pairwise scatter plots and correlation coefficients

Examples

library("airway")
data("airway", package = "airway")
airway
dds_airway <- DESeq2::DESeqDataSetFromMatrix(assay(airway),
                                             colData = colData(airway),
                                             design = ~dex+cell)
pair_corr(counts(dds_airway)[1:100, ]) # use just a subset for the example

federicomarini/pcaExplorer documentation built on Sept. 29, 2024, 9:31 p.m.