Description Usage Arguments Details Value See Also Examples

This function converts an instance of `AffyBatch`

into an instance of `exprSet-class`

using a factor analysis model
for which a Bayesian Maximum a Posteriori method optimizes the model parameters under
the assumption of Gaussian measurement noise. This function is a wrapper for `expresso`

and uses the function `normalize.quantiles`

for array normalization.

1 2 | ```
qFarms(object, weight, mu, weighted.mean, laplacian, robust, correction, centering, spuriousCorrelation, ...)
``` |

`object` |
An instance of |

`weight` |
Hyperparameter value in the range of [0,1] which determines the influence of the prior. The default value is 0.5 |

`mu` |
Hyperparameter value which allows to quantify different aspects of potential prior knowledge. Values near zero assumes that most genes do not contain a signal, and introduces a bias for loading matrix elements near zero. Default value is 0 |

`weighted.mean` |
Boolean flag, that indicates whether a weighted mean or a least square fit is used to summarize the loading matrix. The default value is set to FALSE. |

`laplacian` |
Boolean flag, indicates whether a Laplacian prior for the factor is employed or not. Default value is FALSE. |

`robust` |
Boolean flag, that ensures non-constant results. Default value is TRUE. |

`correction` |
Value that indicates whether the covariance matrix should be corrected for negative eigenvalues which might emerge from the non-negative correlation constraints or not. Default = O (means that no correction is done), 1 (minimal noise (0.0001) is added to the diagonal elements of the covariance matrix to force positive definiteness), 2 (Maximum Likelihood solution to compute the nearest positive definite matrix under the given non-negative correlation constraints of the covariance matrix) |

`centering` |
Indicates whether the data is "median" or "mean" centered. Default value is "median". |

`spuriousCorrelation` |
Numeric value in the range of [0,1] that quantifies the suppression of spurious correlation when using the Laplacian prior. Default value is 0 (no suppression). Note, that this parameter is only active when the laplacian parameter is set to TRUE. |

`...` |
other arguments to be passed to |

This function is a wrapper for `expresso`

.

`exprSet-class`

`expresso`

, `expFarms`

, `lFarms`

, `normalize.quantiles`

1 2 | ```
data(testAffyBatch)
eset <- qFarms(testAffyBatch)
``` |

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