XDE (version 2.18.0)

ssStatistic: Calculate single study estimates of effect size

Description

Calculate single study estimates of effect size for lists of ExpressionSets

Usage

ssStatistic(statistic = c("t", "sam", "z")[1], phenotypeLabel, esetList, ...)

Arguments

statistic

Character string indicating Welch t-statistic (t), SAM (sam), or a z-statistic (z)

phenotypeLabel

Character string indicating the name of the binary covariate

esetList

An object of class ExpressionSetList

...

Not implemented. Potentially additional arguments to the above methods that are implemented in other packages

Value

A matrix: rows are genes and columns are studies

Details

This function is a wrapper that provides an estimate of effect size for each study (element) in an ExpressionSetList object.

For Welch t-statistic, this function is a wrapper for mt.teststat in the multtest package. For SAM, this function is a wrapper for the sam function in the siggenes package.

The "z" statistic is a standardized unbiased estimate of effect size (Hedges and Olkin, 1985) -- implementation is in the zScores function in the R package GeneMeta.

See the complete references below.

References

J.K. Choi, U. Yu, S. Kim, and O.J. Yoo (2003), Combining multiple microarray studies and modeling interstudy variation, Bioinformatics, 19(1) I84-I90.

Y. Ge, S. Dudoit & T. P. Speed (2003), Resampling-based multiple testing for microarray data hypothesis Test 12(1) : 1-44 (with discussions on 44-77).

L. Lusa R. Gentleman, and M. Ruschhaupt, GeneMeta: MetaAnalysis for High Throughput Experiments

L.V. Hedges and I. Olkin, Statistical Methods for Meta-analysis (1985), Academic Press

Tusher, Tibshirani and Chu (2001), Significance analysis of microarrays applied to the ionizing radiation response, PNAS 2001 98: 5116-5121, (Apr 24).

Examples

data(expressionSetList)
if(require(siggenes)){
  sam <- ssStatistic("sam", esetList=expressionSetList, phenotypeLabel="adenoVsquamous")
}