copaStat

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Description

Calculates outlier statistics by the Tibshirani-Hastie method

Usage

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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

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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')