xde {XDE} | R Documentation

## 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`.

### 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.

### Value

Object of class `XdeMcmc`

### Note

See the vignettes for XdeParameterClass and XDE.

### Author(s)

R. Scharpf

### 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)

[Package XDE version 2.40.0 Index]