exp.farms {farms}R Documentation

Factor Analysis for Robust Microarray Summarization

Description

This function converts an instance of AffyBatch-class{AffyBatch.Rdash.class} into an instance of exprSet-class{exprSet.Rdash.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.

Usage

          exp.farms(object, bgcorrect.method = "none", pmcorrect.method = "pmonly", 
        normalize.method = "quantiles",  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.
bgcorrect.method the name of the background adjustment method
pmcorrect.method the name of the PM adjustement method
normalize.method the normalization method to use
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, q.farms, l.farms.

Examples

  data(affybatch.example)
  eset <- exp.farms(affybatch.example, weight=8, scale=1.5)

[Package farms version 1.3 Index]