padmaRun {padma} | R Documentation

## Calculate individualized deviation scores from multi-omic data

### Description

Calculate individualized deviation scores from multi-omic data

### Usage

    padmaRun(
      omics_data,
      gene_map = padma::mirtarbase,
      base_ids = NULL,
      supp_ids = NULL,
      pathway_name = "c2_cp_BIOCARTA_D4GDI_PATHWAY",
      impute = FALSE,
      variance_threshold = 1e-04,
      full_results = TRUE,
      verbose = TRUE,
      ...
    )

### Arguments

`omics_data` | Object of class `'MultiAssayExperiment'` containing omics data from n matched individuals.
`gene_map` | (optional) Data frame mapping arbitrary biological entities (e.g. miRNAs) to genes. Contains two columns, where the first provides the IDs of the entity and the second provides the IDs of the corresponding target gene. By default, the miRNA-gene interactions of type 'Functional MTI' from miRTarBase are used (see the preloaded `'mirtarbase'` data in the package).
`base_ids` | (optional) Sample names to be used as reference base data. By default, all samples are used.
`supp_ids` | (optional) Sample names to be used as supplementary individuals to be projected onto the analysis based on the individuals identified in `base_ids`. By default, takes the value `NULL`, but should not overlap with `base_ids` if provided by the user.
`pathway_name` | Character of either a KEGG pathway identifier or MSigDB pathway names (e.g., see the pathway names in the `'geneset'` column of the preloaded `msigdb` data in the package), or a vector of gene symbols.
`impute` | If `TRUE`, impute missing values separately in base and supplementary data using MFA as implemented in the missMDA package; otherwise simple mean imputation is used (default).
`variance_threshold` | Minimal variance required across samples to retain a biological entity in the analysis
`full_results` | If `TRUE` (default), include full MFA results in function output; otherwise, provide concise output to save space.
`verbose` | If `TRUE`, provide verbose output.
`...` | Optional additional arguments

### Value

An S4 object of class `padmaResults`, where individualized pathway deviation scores are stored as the assay data, and the corresponding pathway name, full MFA results, number of genes, and names of imputed or filtered genes are stored as slots that can be retrieved using the appropriate accessor functions.

### 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]