runNMDS: Perform non-metric MDS on sample-level data

In microbiome/mia: Microbiome analysis

Perform non-metric MDS on sample-level data

Description

Perform non-metric multi-dimensional scaling (nMDS) on samples, based on the data in a SingleCellExperiment object.

Usage

calculateNMDS(x, ...)

## S4 method for signature 'ANY'
calculateNMDS(
  x,
  FUN = vegdist,
  nmdsFUN = c("isoMDS", "monoMDS"),
  ncomponents = 2,
  ntop = 500,
  subset_row = NULL,
  scale = FALSE,
  transposed = FALSE,
  keep_dist = FALSE,
  ...
)

## S4 method for signature 'SummarizedExperiment'
calculateNMDS(
  x,
  ...,
  assay.type = assay_name,
  assay_name = exprs_values,
  exprs_values = "counts",
  FUN = vegdist
)

## S4 method for signature 'SingleCellExperiment'
calculateNMDS(
  x,
  ...,
  assay.type = assay_name,
  assay_name = exprs_values,
  exprs_values = "counts",
  dimred = NULL,
  n_dimred = NULL,
  FUN = vegdist
)

runNMDS(x, ..., altexp = NULL, name = "NMDS")

Arguments

x	For calculateNMDS, a numeric matrix of expression values where rows are features and columns are cells. Alternatively, a TreeSummarizedExperiment containing such a matrix. For runNMDS a SingleCellExperiment
...	additional arguments to pass to FUN and nmdsFUN.
FUN	a function or character value with a function name returning a dist object
nmdsFUN	a character value to choose the scaling implementation, either “isoMDS” for MASS::isoMDS or “monoMDS” for vegan::monoMDS
ncomponents	Numeric scalar indicating the number of NMDS dimensions to obtain.
ntop	Numeric scalar specifying the number of features with the highest variances to use for dimensionality reduction.
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?
keep_dist	Logical scalar indicating whether the dist object calculated by FUN should be stored as ‘dist’ attribute of the matrix returned/stored by calculateNMDS/ runNMDS.
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.)
dimred	String or integer scalar specifying the existing dimensionality reduction results to use.
n_dimred	Integer scalar or vector specifying the dimensions to use if dimred is specified.
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.

Details

Either MASS::isoMDS or vegan::monoMDS are used internally to compute the NMDS components. If you supply a custom FUN, make sure that the arguments of FUN and nmdsFUN do not collide.

Value

For calculateNMDS, a matrix is returned containing the MDS coordinates for each sample (row) and dimension (column).

Author(s)

Felix Ernst

See Also

MASS::isoMDS, vegan::monoMDS for NMDS component calculation.

plotMDS, to quickly visualize the results.

Examples

# generate some example data
mat <- matrix(1:60, nrow = 6)
df <- DataFrame(n = c(1:6))
tse <- TreeSummarizedExperiment(assays = list(counts = mat),
                                rowData = df)
#
calculateNMDS(tse)

#
data(esophagus)
esophagus <- runNMDS(esophagus, FUN = vegan::vegdist, name = "BC")
esophagus <- runNMDS(esophagus, FUN = vegan::vegdist, name = "euclidean",
                     method = "euclidean")
reducedDims(esophagus)

microbiome/mia documentation built on April 27, 2024, 4:04 a.m.