| runNMDS {mia} | R Documentation |
Perform non-metric multi-dimensional scaling (nMDS) on samples, based on the
data in a SingleCellExperiment object.
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,
...,
abund_values = exprs_values,
exprs_values = "counts",
FUN = vegdist
)
## S4 method for signature 'SingleCellExperiment'
calculateNMDS(
x,
...,
abund_values = exprs_values,
exprs_values = "counts",
dimred = NULL,
n_dimred = NULL,
FUN = vegdist
)
runNMDS(x, ..., altexp = NULL, name = "NMDS")
plotNMDS(x, ..., ncomponents = 2)
x |
For For |
... |
additional arguments to pass to |
FUN |
a |
nmdsFUN |
a |
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 |
abund_values |
a single |
exprs_values |
a single |
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. |
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.
For calculateNMDS, a matrix is returned containing the MDS
coordinates for each sample (row) and dimension (column).
Felix Ernst
MASS::isoMDS,
vegan::monoMDS
for NMDS component calculation.
plotMDS, to quickly visualize the
results.
# generate some example data
mat <- matrix(1:60, nrow = 6)
df <- DataFrame(n = c(1:6))
se <- SummarizedExperiment(assays = list(counts = mat),
rowData = df)
#
calculateNMDS(se)
#
data(esophagus)
esophagus <- runNMDS(esophagus, FUN = vegan::vegdist, name = "BC")
esophagus <- runNMDS(esophagus, FUN = vegan::vegdist, name = "euclidean",
method = "euclidean")
reducedDims(esophagus)