Sample to sample relationship.

Sample to sample relationship.

SampleRelation(
  deobj,
  gene = NULL,
  remove.sample = NULL,
  transform.method = c("rlog", "vst", "ntd"),
  anno.key = NULL,
  ...
)

Arguments

deobj	Object created by DESeq2 or edgeR.
gene	Genes used to create sample relationship. Default: NULL.
remove.sample	Sample(s) to remove. Default: NULL.
transform.method	Data transformation methods, chosen from rlog, vst and ntd. Default: rlog.
anno.key	Group to annotate samples. When set NULL, select first column of metadata. Default: NULL.
...	Parameters for pheatmap.

Value

Plot of sample distances and sample pearson correlation.

Examples

library(DESeq2)
library(DEbPeak)
count.file <- system.file("extdata", "snon_count.txt", package = "DEbPeak")
meta.file <- system.file("extdata", "snon_meta.txt", package = "DEbPeak")
count.matrix <- read.table(file = count.file, header = TRUE, sep = "\t")
meta.info <- read.table(file = meta.file, header = TRUE)
dds <- DESeq2::DESeqDataSetFromMatrix(countData = count.matrix, colData = meta.info, design = ~condition)
#> Warning: some variables in design formula are characters, converting to factors
keep.genes <- rowSums(DESeq2::counts(dds, normalized = FALSE)) >= 10
dds <- dds[keep.genes, ]
SampleRelation(deobj = dds, transform.method = "rlog", anno.key = "condition")
#> Differential expression analysis with DESeq2!