get_pcoa: performs principal coordinate analysis (PCoA)

In xiangpin/MicrobitaProcess: A comprehensive R package for managing and analyzing microbiome and other ecological data within the tidy framework

performs principal coordinate analysis (PCoA)

Description

performs principal coordinate analysis (PCoA)

Usage

get_pcoa(obj, ...)

## S3 method for class 'data.frame'
get_pcoa(
  obj,
  distmethod = "euclidean",
  taxa_are_rows = FALSE,
  sampleda = NULL,
  tree = NULL,
  method = "hellinger",
  ...
)

## S3 method for class 'dist'
get_pcoa(
  obj,
  distmethod,
  data = NULL,
  sampleda = NULL,
  method = "hellinger",
  ...
)

## S3 method for class 'phyloseq'
get_pcoa(obj, distmethod = "euclidean", ...)

Arguments

obj	phyloseq, the phyloseq class or dist class.
...	additional parameter, see also get_dist.
distmethod	character, the method of distance, see also distance
taxa_are_rows	logical, if feature of data is column, it should be set FALSE.
sampleda	data.frame, nrow sample * ncol factor, default is NULL.
tree	phylo, the phylo class, default is NULL, when use unifrac method, it should be required.
method	character, the standardization method for community ecologists, default is hellinger, if the data has be normlized, it shound be set NULL.
data	data.frame, numeric data.frame nrow sample * ncol features.

Value

pcasample object, contained prcomp or pcoa and sampleda (data.frame).

Author(s)

Shuangbin Xu

Examples

## Not run: 
    library(phyloseq)
    data(GlobalPatterns)
    subGlobal <- subset_samples(GlobalPatterns, 
                  SampleType %in% c("Feces", "Mock", "Ocean", "Skin"))
    pcoares <- get_pcoa(subGlobal, 
                       distmethod="euclidean",
                       method="hellinger")
    pcoaplot <- ggordpoint(pcoares, biplot=FALSE,
                            speciesannot=FALSE,
                            factorNames=c("SampleType"), 
                            ellipse=FALSE)

## End(Not run)

xiangpin/MicrobitaProcess documentation built on April 12, 2024, 9:03 p.m.