Calculation of Double Principal Correspondance analysis

Source: R/runDPCoA.R

Double Principal Correspondance analysis is made available via the ade4 package in typical fashion. Results are stored in the reducedDims and are available for all the expected functions.

calculateDPCoA(x, y, ...)

# S4 method for ANY,ANY
calculateDPCoA(
  x,
  y,
  ncomponents = 2,
  ntop = NULL,
  subset_row = NULL,
  scale = FALSE,
  transposed = FALSE,
  ...
)

# S4 method for TreeSummarizedExperiment,missing
calculateDPCoA(
  x,
  ...,
  assay.type = assay_name,
  assay_name = exprs_values,
  exprs_values = "counts",
  tree_name = "phylo"
)

runDPCoA(x, ..., altexp = NULL, name = "DPCoA")

Arguments

x

For calculateDPCoA, a numeric matrix of expression values where rows are features and columns are cells. Alternatively, a TreeSummarizedExperiment containing such a matrix.

For runDPCoA a TreeSummarizedExperiment containing the expression values as well as a rowTree to calculate y using cophenetic.phylo.

y

a dist or a symmetric matrix compatible with ade4:dpcoa

...

Currently not used.

ncomponents

Numeric scalar indicating the number of DPCoA dimensions to obtain.

ntop

Numeric scalar specifying the number of features with the highest variances to use for dimensionality reduction. Alternatively NULL, if all features should be used. (default: ntop = NULL)

subset_row

Vector specifying the subset of features to use for dimensionality reduction. This can be a character vector of row names, an integer vector of row indices or a logical vector.

scale

Logical scalar, should the expression values be standardized?

transposed

Logical scalar, is x transposed with cells in rows?

assay.type

a single character value for specifying which assay to use for calculation.

assay_name

a single character value for specifying which assay to use for calculation. (Please use assay.type instead. At some point assay_name will be disabled.)

exprs_values

a single character value for specifying which assay to use for calculation. (Please use assay.type instead.)

tree_name

a single character value for specifying which rowTree will be used in calculation. (By default: tree_name = "phylo")

altexp

String or integer scalar specifying an alternative experiment containing the input data.

name

String specifying the name to be used to store the result in the reducedDims of the output.

Value

For calculateDPCoA a matrix with samples as rows and CCA dimensions as columns

For runDPCoA a modified x with the results stored in reducedDim as the given name

Details

In addition to the reduced dimension on the features, the reduced dimension for samples are returned as well as sample_red attribute. eig, feature_weights and sample_weights are returned as attributes as well.

Examples

data(esophagus)
dpcoa <- calculateDPCoA(esophagus)
head(dpcoa)
#>          [,1]         [,2]
#> B -0.05368615  0.046589779
#> C -0.04324591 -0.039790060
#> D  0.10011870  0.003144932

esophagus <- runDPCoA(esophagus)
reducedDims(esophagus)
#> List of length 1
#> names(1): DPCoA

library(scater)
plotReducedDim(esophagus, "DPCoA")