Pairwise scatter and correlation plot of counts

Pairwise scatter and correlation plot of counts

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
#> class: RangedSummarizedExperiment 
#> dim: 63677 8 
#> metadata(1): ''
#> assays(1): counts
#> rownames(63677): ENSG00000000003 ENSG00000000005 ... ENSG00000273492
#>   ENSG00000273493
#> rowData names(10): gene_id gene_name ... seq_coord_system symbol
#> colnames(8): SRR1039508 SRR1039509 ... SRR1039520 SRR1039521
#> colData names(9): SampleName cell ... Sample BioSample
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