dist_mass_dataset: dist_mass_dataset

In jaspershen/massstat: Statistical analysis for LC-MS-based metabolomics data

dist_mass_dataset

Description

dist_mass_dataset

Usage

dist_mass_dataset(
  x,
  margin = c("variable", "sample"),
  method = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
  diag = FALSE,
  upper = FALSE,
  p = 2
)

Arguments

x	mass_dataset class
margin	sample or variable
method	the distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski". Any unambiguous substring can be given.
diag	logical value indicating whether the diagonal of the distance matrix should be printed by print.dist.
upper	logical value indicating whether the upper triangle of the distance matrix should be printed by print.dist.
p	The power of the Minkowski distance.

Value

dist returns an object of class "dist".

Author(s)

Xiaotao Shen [e-mail]

Examples

library(massdataset)
library(magrittr)
data("expression_data")
data("sample_info")
data("sample_info_note")
data("variable_info")
data("variable_info_note")
object =
  create_mass_dataset(
    expression_data = expression_data,
    sample_info = sample_info,
    variable_info = variable_info,
    sample_info_note = sample_info_note,
    variable_info_note = variable_info_note
  )
object
x =
  object %>%
  log(2) %>%
  scale()
variable_distance <-
  dist_mass_dataset(x = x, margin = "variable")
head(as.matrix(variable_distance)[, 1:5])
sample_distance <-
  dist_mass_dataset(x = x, margin = "sample")
head(as.matrix(sample_distance)[, 1:5])

jaspershen/massstat documentation built on Sept. 29, 2022, 4:30 a.m.