getPathpVals: Extract Table of p-values from a 'superpcOut'- or 'aespcOut'-...

In pathwayPCA: Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection

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
  )

pathwayPCA documentation built on Dec. 15, 2020, 6:14 p.m.