copaStat {OGSA} | R Documentation

## copaStat

### Description

Calculates outlier statistics by the Tibshirani-Hastie method

### Usage

    copaStat (data, phenotype, tail='right', perms=100, permType='array')

### Arguments

`data` | A matrix of nGene by nSample
`phenotype` | A vector of 0s and 1s of length nSample, where 1 = case, 0 = control
`tail` | Indicates whether outliers are up (right) or down (left) outliers
`perms` | The number of permutations
`permType` | By all on array or by gene, if by gene increase perms significantly and plan on lots of time; in theory array should be fine as genes are rescaled

### Value

A vector with outlier counts by gene

### References

Ochs, M. F., Farrar, J. E., Considine, M., Wei, Y., Meshinchi, S., & Arceci, R. J. (n.d.). Outlier Analysis and Top Scoring Pair for Integrated Data Analysis and Biomarker Discovery. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1-1. doi:10.1109/tcbb.2013.153

### Examples

    data(ExampleData)

    #Set up phenotype
    phenotype <- pheno
    names(phenotype) <- colnames(cnv)

    #set up values for expr-meth-cnv in that order
    tailLRL <- c('left', 'right', 'left')

    #setup dataList
    dataSet <- list(expr, meth, cnv)

    data <- dataSet[[1]]

    tibL <- copaStat(data, phenotype, tail='right', perms=100, permType='array')

[Package OGSA version 1.16.0 Index]