getPathpVals {pathwayPCA} | R Documentation

## Extract Table of p-values from a `superpcOut`- or `aespcOut`- class Object.

### Description

Given an object of class `aespcOut` or `superpcOut`, as returned by the functions `AESPCA_pVals` or `SuperPCA_pVals`, respectively, return a data frame of the p-values for the top pathways.

### Usage

    getPathpVals(pcOut, score = FALSE, numPaths = 20L, alpha = NULL, ...)

    ## S3 method for class 'superpcOut'
    getPathpVals(pcOut, score = FALSE, numPaths = 20L, alpha = NULL, ...)

    ## S3 method for class 'aespcOut'
    getPathpVals(pcOut, score = FALSE, numPaths = 20L, alpha = NULL, ...)

### Arguments

`pcOut` | An object of classes `superpcOut` or `aespcOut` as returned by the `SuperPCA_pVals` or `AESPCA_pVals` functions, respectively.
`score` | Should the unadjusted p-values be returned transformed to negative natural logarithm scores or left as is? Defaults to `FALSE`; that is, the raw p-values are returned instead of the transformed p-values.
`numPaths` | The number of top pathways by raw p-value. Defaults to the top 20 pathways. We do not permit users to specify `numPaths` and `alpha` concurrently.
`alpha` | The significance threshold for raw p-values. Defaults to `NULL`. If `alpha` is given, then `numPaths` will be ignored.
`...` | Dots for additional arguments (currently unused).

### Details

Row-subset the `pVals_df` entry of an object of class `aespcOut` or `superpcOut` by the number of pathways requested (via the `nPaths` argument) or by the unadjusted significance level for each pathway (via the `alpha` argument). Return a data frame of the pathway names, FDR-adjusted significance levels (if available), and the raw score (negative natural logarithm of the p-values) of each pathway.

### Value

A data frame with the following columns:

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

- `description` : (OPTIONAL) The pathway description, as given in the `object@trimPathwayCollection$description` object, if supplied.

- `rawp` : The unadjusted p-values of each pathway. Included if `score = FALSE`.

- `...` : Additional columns of FDR-adjusted p-values as specified through the `adjustment` argument of the `SuperPCA_pVals` or `AESPCA_pVals` functions.

- `score` : The negative natural logarithm of the unadjusted p-values of each pathway. Included if `score = TRUE`.

`NULL`

`NULL`

### Examples

      ###  Load Data  ###
      data("colonSurv_df")
      data("colon_pathwayCollection")

      ###  Create -Omics Container  ###
      colon_Omics <- CreateOmics(
        assayData_df = colonSurv_df[, -(2:3)],
        pathwayCollection_ls = colon_pathwayCollection,
        response = colonSurv_df[, 1:3],
        respType = "survival"
      )

      ###  Calculate Supervised PCA Pathway p-Values  ###
      colon_superpc <- SuperPCA_pVals(
        colon_Omics,
        numPCs = 2,
        parallel = TRUE,
        numCores = 2,
        adjustment = "BH"
      )

      ###  Extract Table of p-Values  ###
      # Top 5 Pathways
      getPathpVals(
        colon_superpc,
        numPaths = 5
      )

      # Pathways with Unadjusted p-Values < 0.01
      getPathpVals(
        colon_superpc,
        alpha = 0.01
      )

[Package pathwayPCA version 1.10.0 Index]