RHT.fun: One-sample Regularized Hotelling's T-square Test

In RHT: Regularized Hotelling's T-square Test for Pathway (Gene Set) Analysis

Description

This function tests if a pathway (or gene set) consists of any protein (or gene) that shows non-zero abundance (or expression).

Usage

RHT.fun(path.idx, dat, nsim = 1000, seed = 123)

Arguments

path.idx	This is a LIST. Each element in the list contains the indice of proteins (or genes) for a pathway in the data set.
dat	An N by p matrix of protein abundance (or gene expression). Each row represents one sample and each column represents a protein (or a gene).
nsim	Number of resamples needed to calculate the p-value. By default, nsim=1000.
seed	A single integer that controls the random number generator in the resampling.

Value

The function returns the p-values for each pathway in the list path.idx.

Author(s)

Lin S Chen and Pei Wang

References

Chen LS, Paul D, Prentice RL and Wang P. (2011) A regularized Hotelling's T-square test for pathway analysis in proteomics studies. Journal of the American Statistical Association, in press.

See Also

See Also RHT.2samp

Examples

  ## we simulate a data set with N=10 samples and p=50 proteins. 
  ## 20% of the data are missing.
  ## Among the 50 proteins, we randomly assign 2 pathways, with 5 and 12 proteins, respectively.
  
  set.seed(1)
  X <- matrix(rnorm(500),nrow=10)
  X[sample(1:500, 0.2*500)] <- NA
  path.idx <- list()
  path.idx[[1]] <- 1:5
  path.idx[[2]] <- 13:24
  names(path.idx) <- c("pathway A", "pathway B")
  
  ## The following function tests each pathway to see
  ## if any of the proteins in each pathway shows non-zero 
  ## abundance/expression
  
  pval <- RHT.fun(path.idx, dat=X)

RHT documentation built on May 2, 2019, 8:25 a.m.