Mult-Omic data integration

This function performs multi-omic integration of Spatial Metabolomics and Spatial Transcriptomics data using Seurat's Weighted Nearest Neighbours function.

Usage

MultiOmicIntegration(
  multiomic.data,
  weight.list = NULL,
  reduction.list = list("spt.pca", "spm.pca"),
  dims.list = list(1:30, 1:30),
  return.intermediate = FALSE,
  verbose = FALSE,
  ...
)

Arguments

multiomic.data

SpaMTP dataset contain Spatial Transcriptomics and Metabolomic datasets in two different assays

weight.list

List containing the relative weightings for each modality, matching the reduction order. If NULL, weights will be automatically calculated else, two values must add to 1 (default = NULL).

reduction.list

List containing character strings defining the reduction to use for each modality, in the order matching weight.list if applicable (default = list("spt.pca", "spm.pca")).

dims.list

List containing the numeric range of principle component dimension to include for each modality (default = list(1:30,1:30)).

return.intermediate

Boolean value indicating whether to store intermediate results in misc slot of SpaMTP Seurat class object (default = FALSE).

verbose

Boolean indicating whether to show the message. If TRUE the message will be show, else the message will be suppressed (default = TRUE).

...

Additional arguments that can be parsed through Seurat's FindMultModalNeighbors function. For possible inputs please visit: https://www.rdocumentation.org/packages/Seurat/versions/5.0.3/topics/FindMultiModalNeighbors.

Value

SpaMTP Seurat class object containing a weighted nearest neighbours graph which integrates Metabolic and Transcriptomic modalities. This graph can be used for clustering.

Examples

# SpaMTP.obj <- MultiOmicIntegration(SpaMTP.obj, weight.list = list(0.5, 0.5), reduction.list =  list("spt.pca", "spm.pca"), dims.list = list(1:30, 1:30))