RandomScore: Function to do compute random and subsampled similarity score

In MAMA: Meta-Analysis of MicroArray

Description

Function computes random and subsampled similarity score in order to select appropriate tunning parameter alpha for weights in preliminary simmilarity score

Usage

RandomScore(data, varname, B, alpha, test, which = c("random", "empirical", "subsample"), two.sided = TRUE)

Arguments

data	MetaArray object
varname	String indicating which column of clinical data should be used as class labels, same on all data set
B	Number of permutation
alpha	Vector of alphas considered (can be returned by computeAlpha) or selected manually
test	"FCH" for fold change (function fold.change) or "T" for T-test (function meta.test)
which	"random" for random score (permutation of class labels), "subsample" for subsampled score, "empirical" for empirical confidence intervals of overalaping genes, vector of several is also possible
two.sided	if TRUE both top and bottom of the ordering considered, if FALSE only top positions are considered

Value

A list

random	Random similarity score
empirical	Empirical confidence intervals for overlaping genes
subsample	Subsampled score

Author(s)

Ivana Ihnatova

MAMA documentation built on Jan. 15, 2017, 3:05 p.m.