Pairwise scatter plot matrix and correlation plot of counts

Usage

pair_corr(df, log = TRUE, 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 TRUE.
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("macrophage")
library("DESeq2")
data(gse, package = "macrophage")
## dds object
dds_macrophage <- DESeqDataSet(gse, design = ~ line + condition)
#> using counts and average transcript lengths from tximeta
rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15)
dds_macrophage <- estimateSizeFactors(dds_macrophage)
#> using 'avgTxLength' from assays(dds), correcting for library size

## Using just a subset for the example
pair_corr(counts(dds_macrophage, normalized = TRUE)[1:100, 1:8])