pair_corr {pcaExplorer} | R Documentation

## 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)
    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

[Package pcaExplorer version 2.20.2 Index]