Description Usage Arguments Details Value Note Author(s) References See Also Examples

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

1 2 |

`paramsMcmc` |
Object of class |

`esetList` |
Object of class |

`outputMcmc` |
Object of class |

`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 |

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.

Object of class `XdeMcmc`

See the vignettes for XdeParameterClass and XDE.

R. Scharpf

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

`XdeMcmc-class`

, `XdeParameter-class`

, `ExpressionSetList-class`

1 2 3 4 5 6 7 | ```
## Not run:
data(expressionSetList)
xparam <- new("XdeParameter", phenotypeLabel="adenoVsquamous", esetList=expressionSetList)
iterations(xparam) <- 10
fit <- xde(xparam, esetList=expressionSetList)
## End(Not run)
``` |

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