Perform non-metric multi-dimensional scaling (nMDS) on samples, based on the
data in a SingleCellExperiment object.
getNMDS(x, ...)
# S4 method for class 'ANY'
getNMDS(
x,
FUN = vegdist,
nmds.fun = nmdsFUN,
nmdsFUN = c("isoMDS", "monoMDS"),
ncomponents = 2,
ntop = 500,
subset.row = subset_row,
subset_row = NULL,
scale = FALSE,
transposed = FALSE,
keep.dist = keep_dist,
keep_dist = FALSE,
...
)
# S4 method for class 'SummarizedExperiment'
getNMDS(
x,
...,
assay.type = assay_name,
assay_name = exprs_values,
exprs_values = "counts",
FUN = vegdist
)
# S4 method for class 'SingleCellExperiment'
getNMDS(
x,
...,
assay.type = assay_name,
assay_name = exprs_values,
exprs_values = "counts",
dimred = NULL,
ndimred = n_dimred,
n_dimred = NULL,
FUN = vegdist
)
calculateNMDS(x, ...)
addNMDS(x, ..., altexp = NULL, name = "NMDS")
runNMDS(x, ...)additional arguments to pass to FUN and
nmds.fun.
Function or Character scalar. A value with a function
name returning a dist object
Character scalar. A value to choose the scaling
implementation, either “isoMDS” for
MASS::isoMDS or “monoMDS” for
vegan::monoMDS
Deprecated. Use nmds.fun instead.
Numeric scalar. Indicates the number of DPCoA dimensions
to obtain. (Default: 2)
Numeric scalar. Specifies the number of features with the highest
variances to use for dimensionality reduction. Alternatively NULL,
if all features should be used. (Default: NULL)
Character Vector. Specifies 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. (Default: NULL)
Deprecated. Use subset.row instead.
Logical scalar. Should the expression values be standardized?
(Default: FALSE)
Logical scalar. Specifies if x is transposed with
cells in rows. (Default: FALSE)
Logical scalar. Indicates whether the dist object
calculated by FUN should be stored as ‘dist’ attribute of
the matrix returned/stored by getNMDS/ addNMDS. (Default:
FALSE)
Deprecated. Use keep.dist instead.
Character scalar. Specifies which assay to use for
calculation. (Default: "counts")
Deprecated. Use assay.type instead.
Deprecated. Use assay.type instead.
Character scalar or integer scalar. Specifies the existing dimensionality
reduction results to use.
integer vector. Specifies the dimensions to use if
dimred is specified.
Deprecated. Use ndimred instead.
Character scalar or integer scalar. Specifies an
alternative experiment containing the input data. (Default: NULL)
Character scalar. A name for the column of the
colData where results will be stored. (Default: "NMDS")
For getNMDS, a matrix is returned containing the MDS
coordinates for each sample (row) and dimension (column).
For addNMDS a SingleCellExperiment
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 nmds.fun do not collide.
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))
tse <- TreeSummarizedExperiment(assays = list(counts = mat),
rowData = df)
#
getNMDS(tse)
#> initial value 0.383462
#> iter 5 value 0.161655
#> iter 10 value 0.113278
#> final value 0.003270
#> converged
#> [,1] [,2]
#> [1,] -0.60647893 0.282119175
#> [2,] -0.38097446 -0.130374816
#> [3,] -0.17579928 -0.184259003
#> [4,] -0.02959516 -0.158516980
#> [5,] 0.09082607 -0.111879947
#> [6,] 0.14427170 -0.047910688
#> [7,] 0.20118089 -0.001837781
#> [8,] 0.22817639 0.061022767
#> [9,] 0.25717122 0.116809029
#> [10,] 0.27122156 0.174828245
#> attr(,"Stress")
#> [1] 0.003269857
#
data(esophagus)
esophagus <- addNMDS(esophagus, FUN = vegan::vegdist, name = "BC")
#> initial value 0.000000
#> final value 0.000000
#> converged
esophagus <- addNMDS(esophagus, FUN = vegan::vegdist, name = "euclidean",
method = "euclidean")
#> initial value 0.000000
#> final value 0.000000
#> converged
reducedDims(esophagus)
#> List of length 2
#> names(2): BC euclidean