RNAgamma: RNA gamma
In GSAgm: Gene Set Analysis using the Gamma Method

Description Usage Arguments Examples

View source: R/RNAgamma.R

For GSA of RNA-seq data, the following procedure, similar to the analysis of SNP data, is implemented (see Fridley et al[2] for more details on the method). Step 1: Association of gene expression data from RNA-seq (count data) is assessed for differential expression between two groups using edgeR[3]. Step 2: P-values from the association analysis within edgeR for genes within a given gene set are combined using the Gamma Method to determine the association of the gene set with the phenotype. Currently, the RNA-seq GSA allows only a binary phenotype (i.e, treatment, control).

1 2	RNAgamma(formula, data, rnaprefix="ENSG", gammaShape=1,STT=NULL, pheno.type=c("case.control"),tagwise=F,perm=T,n.perm=1000,seed=12212012)

`formula`	formula in R format: phenotype~cov1+cov2
`data`	data frame containing phenotype, covars, and RNA stuff
`rnaprefix`	RNA data prefix, defaults to ENSG ensembl genes
`gammaShape`	numeric indicating the gamma shape parameter to be used for p-value summarization
`STT`	numeric indicating soft truncation threshold to be used, will calculate gamma parameter (must be <= 0.4)
`pheno.type`	type of phenotype, case-control results in logistic regression, quantitative results in OLS, and survival results in cox model
`tagwise`	TRUE or FALSE for estimating tagwise dispersion values by an empirical Bayes method based on weighted conditional maximum likelihood. Defaults to maximizing the negative binomial conditional common likelihood for the common dispersion across all tags.
`perm`	boolean indicating whether permutation p-value are to be used for the gamma summary method
`n.perm`	numeric indicating number of permutations to be used
`seed`	numeric to set RNG for reproducability

data(testdata)
data(rnaseq_counts)
testdata <- cbind(testdata,rnaseq_counts)
RNAgamma(pheno~strata(study)+age, data=testdata, rnaprefix="rnaseqcount", 
         pheno.type=c("case.control"),tagwise=FALSE,perm=TRUE,n.perm=5)

##No covars, no permutation
RNAgamma(pheno~., data=testdata, rnaprefix="rnaseqcount", 
         pheno.type=c("case.control"),tagwise=FALSE,perm=FALSE)