Transforms the output of an analysis with limma into a `SAM`

or `EBAM`

object, such that a SAM or EBAM analysis, respectively,
can be performed using the test statistics provided by limma.

1 2 3 4 | ```
limma2sam(fit, coef, moderate = TRUE, sam.control = samControl())
limma2ebam(fit, coef, moderate = TRUE, delta = 0.9,
ebam.control = ebamControl())
``` |

`fit` |
an object of class |

`coef` |
column number or name corresponding to the coefficient or contrast of
interest. For details, see the argument |

`moderate` |
should the limma t-statistic be considered? If |

`sam.control` |
further arguments for the SAM analysis. See |

`delta` |
the minimum posterior probability for a gene to be called differentially
expressed (or more generally, for a variable to be called significant) in an EBAM
analysis. For details, see |

`ebam.control` |
further arguments for an EBAM analysis. See |

An object of class `SAM`

or `EBAM`

.

Holger Schwender, holger.schwender@udo.edu

Efron, B., Tibshirani, R., Storey, J.D. and Tusher, V. (2001). Empirical Bayes Analysis
of a Microarray Experiment. *JASA*, 96, 1151-1160.

Smyth, G.K. (2004). Linear Models and Empirical Bayes Methods for Assessing Differential
Expression in Microarray Experiments. *Statistical Applications in Genetics and
Molecular Biology*, 3(1), Article 3.

Tusher, V.G., Tibshirani, R., and Chu, G. (2001). Significance Analysis of Microarrays
Applied to the Ionizing Radiation Response. *PNAS*, 98, 5116-5121.

`sam`

, `ebam`

, `SAM-class`

, `EBAM-class`

,
`samControl`

, `ebamControl`

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