transformSpataToCDS: Transform spata-object to cell-data-set (Monocle3)
In kueckelj/SPATA2: A Toolbox for Spatial Gene Expression Analysis

transformSpataToCDS

R Documentation

Transform spata-object to cell-data-set (Monocle3)

Description

Takes the count matrix of your spata-object and creates a cell_data_set-object with it. See details for more information on how to use the arguments.

Usage

transformSpataToCDS(
  object,
  preprocess_method = "PCA",
  reduction_method = c("PCA", "UMAP"),
  cluster_method = "leiden",
  estimate_size_factors = list(),
  preprocess_cds = list(),
  reduce_dimension = list(),
  cluster_cells = list(),
  learn_graph = list(),
  order_cells = list(),
  of_sample = NA,
  verbose = TRUE
)

Arguments

`object`	An object of class `spata2`.
`preprocess_method`	Monocle3 - description: A string specifying the initial dimension method to use, currently either PCA or LSI. For LSI (latent semantic indexing), it converts the (sparse) expression matrix into tf-idf matrix and then performs SVD to decompose the gene expression / cells into certain modules / topics. Default is "PCA".
`reduction_method`	Monocle3 - description: A character string specifying the algorithm to use for dimensionality reduction. Currently "UMAP", "tSNE", "PCA" and "LSI" are supported.
`cluster_method`	Monocle3 - description: String indicating the clustering method to use. Options are "louvain" or "leiden". Default is "leiden". Resolution parameter is ignored if set to "louvain".
`verbose`	Logical. If set to TRUE informative messages regarding the computational progress will be printed. (Warning messages will always be printed.)
`estimate_size_factors_args`	A list of arguments given to `monocle3::estimate_size_factors()`.
`preprocess_cds_args`	A list of arguments given to `monocle3::preprocess_cds()`.
`reduce_dimension_args`	A list of arguments given to `monocle3::reduce_dimension()`.
`cluster_cells_args`	A list of arguments given to `monocle3::cluster_cells()`.
`learn_graph_args`	A list of arguments given to `monocle3::learn_graph()`.
`order_cells_args`	A list of arguments given to `monocle3::order_cells()`.
`save_cds_file`	Character value or NULL. A file-directory (that does not already exists) under which created cell_data_set-object is saved. Should end with '.RDS'.

Details

compileCellDataSet() is a convenient wrapper around all pre processing functions monocle3 provides to handle it's core object - the cell_data_set - after it's initiation. Apart from object and of_sample arguments this function has two argument families.

Handling *_method-arguments:

Monocle3 allows to use different methods for dimensional-reduction or clustering which depend on each other. These arguments take a character vector of all valid inputs. transformSpataToCDS() iterates over all valid combinations and returns the cell_data_set with the computed information inside.

Handling monocle-function-arguments:

These arguments take named lists of arguments that are given to the respective function. The _method-arguments as well as the argument cds are automatically defined and must not be included in the given lists!!! Empty lists - the default - result in running the function with it's default parameters.

The spata-objects feature data (@fdata) is passed to the cell_data_set for it's slot cell_meta_data.