q.farms {farms}R Documentation

q.farms expression measure

Description

This function converts an instance of AffyBatch-class 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.

Usage

          q.farms(object, weight, mu, scale, cyc, tol=,...)
          

Arguments

object An instance of AffyBatch-class{AffyBatch.Rdash.class}.
weight Hyperparameter value which determines the influence of the prior.
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.
scale Value which compensates for the reduction of variance during preprocessing and factor analysis (some of the data variance is explained by the noise).
cyc Value which determinates the maximum numbers of EM-Steps.
tol Value which determinates the termination tolerance.
... other arguments to be passed to expresso{expresso}.

Details

This function is a wrapper for expresso.

Value

exprSet-class

See Also

expresso, exp.farms, l.farms, normalize.quantiles

Examples

  data(affybatch.example)
  eset <- q.farms(affybatch.example)

[Package farms version 1.3 Index]