wrap.DiffusionMap: From destiny: Wrapper to create a diffusion map of cells.
In soedinglab/merlot: MERLoT

The provided data can be a double matrix of expression data or a data.frame with all non-integer (double) columns being treated as expression data features (and the others ignored), an ExpressionSet, or a SingleCellExperiment.

wrap.DiffusionMap(data = destiny:::stopifnot_distmatrix(distance),
  sigma = "local", k = destiny::find_dm_k(dataset_n_observations(data,
  distance) - 1L), n_eigs = min(20L, dataset_n_observations(data,
  distance) - 2L), density_norm = TRUE, ..., distance = c("euclidean",
  "cosine", "rankcor"), n_local = seq(to = min(k, 7L), length.out =
  min(k, 3L)), rotate = FALSE, censor_val = NULL,
  censor_range = NULL, missing_range = NULL, vars = NULL,
  verbose = !is.null(censor_range), suppress_dpt = FALSE)

`data`	Expression data to be analyzed and covariates. Provide `vars` to select specific columns other than the default: all double value columns. If `distance` is a distance matrix, `data` has to be a `data.frame` with covariates only.
`sigma`	Diffusion scale parameter of the Gaussian kernel. One of `'local'`, `'global'`, a (numeric) global sigma or a Sigmas object. When choosing `'global'`, a global sigma will be calculated using `find_sigmas`. (Optional. default: `'local'`) A larger sigma might be necessary if the eigenvalues can not be found because of a singularity in the matrix
`k`	Number of nearest neighbors to consider (default: a guess betweeen 100 and n - 1. See `find_dm_k`).
`n_eigs`	Number of eigenvectors/values to return (default: 20)
`density_norm`	logical. If TRUE, use density normalisation
`...`	Unused. All parameters to the right of the `...` have to be specified by name (e.g. `DiffusionMap(data, distance = 'cosine')`)
`distance`	Distance measurement method applied to `data` or a distance matrix/`dist`. For the allowed values, see `find_knn`
`n_local`	If `sigma == 'local'`, the `n_local`th nearest neighbor(s) determine(s) the local sigma
`rotate`	logical. If TRUE, rotate the eigenvalues to get a slimmer diffusion map
`censor_val`	Value regarded as uncertain. Either a single value or one for every dimension (Optional, default: censor_val)
`censor_range`	Uncertainity range for censoring (Optional, default: none). A length-2-vector of certainty range start and end. TODO: also allow 2\times G matrix
`missing_range`	Whole data range for missing value model. Has to be specified if NAs are in the data
`vars`	Variables (columns) of the data to use. Specifying NULL will select all columns (default: All floating point value columns)
`verbose`	Show a progressbar and other progress information (default: do it if censoring is enabled)
`suppress_dpt`	Specify TRUE to skip calculation of necessary (but spacious) information for `DPT` in the returned object (default: FALSE)