TabulatepValues {pathwayPCA} | R Documentation

## Tabulate, adjust, and sort pathway p-values

### Description

Adjust the pathway p-values, then return a data frame of the relevant pathway information, sorted by adjusted significance.

### Usage

    TabulatepValues(pVals_vec, genesets_ls, adjust = TRUE,
      proc_vec = c("BH", "Bonferroni", "Holm", "Hochberg", "SidakSS",
      "SidakSD", "BY", "ABH", "TSBH"), ...)

### Arguments

`pVals_vec` | A named vector of permutation p-values returned by the `PermTestSurv`, `PermTestReg`, or `PermTestCateg` functions when the analysis performed was AES-PCA. Otherwise, when the analysis was performed with Supervised PCA, a named vector of p-values from the `GumbelMixpValues` function.
`genesets_ls` | A list of known gene pathways, trimmed to match the given assay data by the `IntersectOmicsPwyCollct` function. This pathway list must contain: `pathways` : A named list of character vectors where each vector contains the names of the genes in that specific pathway. `TERMS` : A character vector the same length as `pathways` containing the full pathway descriptions. `n_tested` : An integer vector the same length as `pathways` containing the number of genes present in the pathway after trimming. Pathways list trimming is done in the `IntersectOmicsPwyCollct` function.
`adjust` | Should you adjust the p-values for multiple comparisons? Defaults to TRUE.
`proc_vec` | Character vector of procedures. The returned data frame will be sorted in ascending order by the first procedure in this vector, with ties broken by the unadjusted p-value. If only one procedure is selected, then it is necessarily the first procedure. Defaults to `"BH"` (Benjamini and Hochberg, 1995).
`...` | Additional arguments to pass to the `ControlFDR` function.

### Details

This is a wrapper function for the `ControlFDR` function. The number of p-values passed to the `pVals_vec` argument must equal the number of pathways and set size values in the `genesets_ls` argument. If you trimmed a pathway from p- value calculation, then pad this missing value with an `NA`.

### Value

A data frame with columns

- `pathways` : The names of the pathways in the `Omics*` object (stored in `object@trimPathwayCollection$pathways`).

- `n_tested` : The number of genes in each pathway after being trimmed to match the assay. Given in the `n_tested` element of the trimmed pathway collection.

- `terms` : The pathway title, as stored in the `object@trimPathwayCollection$TERMS` object.

- `description` : The pathway description, if it is stored in the `object@trimPathwayCollection$description` object.

- `rawp` : The unadjusted p-values of each pathway.

- `...` : Additional columns as specified through the `adjustment` argument.

The data frame will be sorted in ascending order by the method specified first in the `adjustment` argument. If `adjustpValues = FALSE`, then the data frame will be sorted by the raw p-values. If you have the suggested `tidyverse` package suite loaded, then this data frame will print as a `tibble`. Otherwise, it will stay a simple data frame.

### Examples

      # DO NOT CALL THIS FUNCTION DIRECTLY.
      # Call this function through AESPCA_pVals() or SuperPCA_pVals() instead.

    ## Not run:
      ###  Load the Example Data  ###
      data("colonSurv_df")
      data("colon_pathwayCollection")

      ###  Create an OmicsSurv Object  ###
      colon_Omics <- CreateOmics(
        assayData_df = colonSurv_df[, -(2:3)],
        pathwayCollection_ls = colon_pathwayCollection,
        response = colonSurv_df[, 1:3],
        respType = "surv"
      )

      ###  Extract Pathway PCs and Loadings  ###
      colonPCs_ls <- ExtractAESPCs(
        object = colon_Omics,
        parallel = TRUE,
        numCores = 2
      )

      ###  Pathway p-Values  ###
      pVals <- PermTestSurv(
        OmicsSurv = colon_Omics,
        pathwayPCs_ls = colonPCs_ls$PCs,
        parallel = TRUE,
        numCores = 2
      )

      ###  Create Table of p-Values  ###
      trimmed_PC <- getTrimPathwayCollection(colon_Omics)
      TabulatepValues(
        pVals_vec = pVals,
        genesets_ls = trimmed_PC
      )

    ## End(Not run)

[Package pathwayPCA version 1.2.0 Index]