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Last data update: 2014.03.03

R: Fitting a beta-mixture model to association scores

Arora2010.BMfitting

R Documentation

Fitting a beta-mixture model to association scores

Description

The function fits a three-beta mixture model to functional association scores computed from rich phenotyping screens in Wang X et al., 2012 for RNAi screening data of Ewing's sarcoma in Arora S et al., 2010.

Usage

Arora2010.BMfitting(pheno, model="global", metric="cosine", nPerm=20)

Arguments

`pheno`	a numeric matrix of z-scores with rows and columns corresponding to samples and genes, respectively.
`model`	a character value specifying whether the original (if `global`) or extended (if `stratified`) model is used.
`metric`	a character value specifying the metric to compute similarity scores. Currently, 'cosine' and 'correlation' are supported (see `assoScore` for more details).
`nPerm`	a positive numeric or integer value specifying the number of permutations.

Details

The function implements beta-mixture modelling in the application to Ewing's sarcoma. The function first initiates an object of class BetaMixture with inputted pheno, model and metric. The ‘x’ component of the beta-mixture model is then fitted to permuted data for nPerm times, and the estimated shape parameters of beta distributions are summarized by taking the median values. After fixing the shape parameters of the ‘x’ component, the function invokes fitBM to fit the global or stratified beta-mixture model.

Value

an object of class BetaMixture with beta-mixture modelling results stored at slot result

Author(s)

Xin Wang xw264@cam.ac.uk

References

Arora S, Gonzales IM, Hagelstrom RT, et al. (2010). RNAi phenotype profiling of kinases identifies potential therapeutic targets in Ewing's sarcoma. Molecular Cancer, 9(1), 218.

Wang X, Castro MA, Mulder KW and Markowetz F (2012), Posterior association networks and enriched functional gene modules inferred from rich phenotypic perturbation screens, PLoS Computational Biology, doi:10.1371/journal.pcbi.1002566.

Examples

## Not run: 
data(Arora2010, package="Mulder2012")
BMfitting(pheno=Arora2010, model="global", metric="cosine", nPerm=20)

## End(Not run)