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Run Multi-Omics Integration

Source: R/run_multiomics_integration.R
run_multiomics_integration.Rd

Performs multi-omics integration using one of several available methods: MOFA, MCIA, RGCCA, or DIABLO. This function takes a MultiAssayExperiment object with two or more assays and computes shared latent factors across omics layers.

Usage

run_multiomics_integration(
  expomicset,
  method = "MCIA",
  n_factors = 10,
  scale = TRUE,
  outcome = NULL,
  action = "add"
)

Arguments

expomicset

A MultiAssayExperiment object with at least two assays.

method

Character. Integration method to use. Options are "MOFA", "MCIA", "RGCCA", or "DIABLO".

n_factors

Integer. Number of latent factors/components to compute. Default is 10.

scale

Logical. Whether to scale each assay before integration. Default is TRUE.

outcome

Character. Required if method = "DIABLO". Name of outcome variable in colData used for supervised integration.

action

Character. Whether to "add" results to the metadata or "get" them as a list. Default is "add".

Value

If action = "add", returns a MultiAssayExperiment with integration results stored in metadata(expomicset)$multiomics_integration$integration_results. If action = "get", returns a list with integration method and result.

Details

  • "MOFA" runs Multi-Omics Factor Analysis using the MOFA2 package and returns a trained model.

  • "MCIA" runs multi-co-inertia analysis using the nipalsMCIA package.

  • "RGCCA" runs Regularized Generalized Canonical Correlation Analysis using the RGCCA package.

  • "DIABLO" performs supervised integration using the mixOmics package and a specified outcome.

See also

plot_factor_scores, plot_top_factor_features, run_factor_overlap, run_enrichment

Examples

if (FALSE) { # \dontrun{
expomicset <- run_multiomics_integration(
  expomicset,
  method = "MOFA",
  n_factors = 5,
  scale = TRUE
)

expomicset <- run_multiomics_integration(
  expomicset,
  method = "DIABLO",
  n_factors = 3,
  outcome = "asthma_status"
)
} # }