omicsContrib {padma} | R Documentation

## Plot the omics contribution per MFA axis and the overall weighted contribution

### Description

Plot barplots indicating the percent contribution of each omics to each MFA dimension, as well as the overall weighted (by eigenvalue) percent contribution to the full analysis.

### Usage

    omicsContrib(
      padma_obj,
      max_dim = min(10, nrow(MFA_results(padma_obj)$eig)),
      ggplot = TRUE
    )

### Arguments

`padma_obj` | Output from running the `padma` function (with `'full_results = TRUE'`)
`max_dim` | Maximum dimension number of the MFA to be plotted
`ggplot` | If `TRUE`, use `ggplot2` for plotting (and `cowplot` for combining ggplots)

### Value

Barplots of percent variance contribution, optionally of class `ggplot`.

### Examples

    LUAD_subset <- padma::LUAD_subset
    ## Create MultiAssayExperiment object with LUAD data
    omics_data <-
      list(rnaseq = LUAD_subset$rnaseq,
           methyl = LUAD_subset$methyl,
           mirna = LUAD_subset$mirna,
           cna = LUAD_subset$cna)
    pheno_data <-
      data.frame(LUAD_subset$clinical,
                 row.names = LUAD_subset$clinical$bcr_patient_barcode)
    mae <-
      suppressMessages(
        MultiAssayExperiment::MultiAssayExperiment(
          experiments = omics_data, colData = pheno_data))

    ## Run padma
    run_padma <-
      padma(mae, gene_map = padma::mirtarbase,
            pathway_name = "c2_cp_BIOCARTA_D4GDI_PATHWAY", verbose = FALSE)

    summary(run_padma)

    ## padma plots
    factorMap(run_padma, dim_x = 1, dim_y = 2)
    factorMap(run_padma, dim_x = 1, dim_y = 2,
               partial_id = "TCGA-78-7536")
    omicsContrib(run_padma, max_dim = 10)

[Package padma version 1.0.0 Index]