XDE (version 2.18.0)

xde: Fit the Bayesian hierarchical model for cross-study differential gene expression

Description

Fits the Bayesian hierarchical model for cross-study differential gene expression.

Usage

xde(paramsMcmc, esetList, outputMcmc, batchSize=NULL, NCONC=2, center=TRUE, ...)

Arguments

paramsMcmc

Object of class XdeParameter

esetList

Object of class ExpressionSetList

outputMcmc

Object of class XdeMcmc (optional)

batchSize

Integer or NULL. The number of iterations written to log files before summarizing the chain and then removing. Experimental.

NCONC

The number of studies for which a gene must be differentially expressed in the same direction to be considered as concordantly differentially expressed.

center

Logical. If TRUE, each study is centered to have mean zero.

...

Additional arguments passed to xdeFit.

Value

Object of class XdeMcmc

Details

Details for fitting the Bayesian model are discussed elsewhere (see citation below and XdeParameterClass vignette)

If an integer is specified for the batchSize, summary statistics for the log-files are calculated for every batchSize iterations. The log files are then removed and the next iteration will start a new log file. This allows one to do many iterations without creating enormous log files. This is only reasonable to do if one has already assessed convergence.

References

R. Scharpf et al., A Bayesian Model for Cross-Study Differential Gene Expression, JASA 2009, p1295--1310.

See Also

XdeMcmc-class, XdeParameter-class, ExpressionSetList-class

Examples

## Not run: 
#   data(expressionSetList)
#   xparam <- new("XdeParameter", phenotypeLabel="adenoVsquamous", esetList=expressionSetList)
#   iterations(xparam) <- 10
#   fit <- xde(xparam, esetList=expressionSetList)
# ## End(Not run)