AvgPlm: The AvgPlm class

In aroma.affymetrix: Analysis of Large Affymetrix Microarray Data Sets

The AvgPlm class

Description

Package: aroma.affymetrix
Class AvgPlm

Object
~~|
~~+--ParametersInterface
~~~~~~~|
~~~~~~~+--Model
~~~~~~~~~~~~|
~~~~~~~~~~~~+--UnitModel
~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~+--MultiArrayUnitModel
~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~+--ProbeLevelModel
~~~~~~~~~~~~~~~~~~~~~~~~~~~|
~~~~~~~~~~~~~~~~~~~~~~~~~~~+--AvgPlm

Directly known subclasses:
AvgCnPlm, AvgSnpPlm

public abstract static class AvgPlm
extends ProbeLevelModel

This class represents a PLM where the probe intensities are averaged assuming identical probe affinities. For instance, one may assume that replicated probes with identical sequences have the same probe affinities, cf. the GenomeWideSNP_6 chip type.

Usage

AvgPlm(..., flavor=c("median", "mean"))

Arguments

...	Arguments passed to ProbeLevelModel.
flavor	A character string specifying what model fitting algorithm to be used. This makes it possible to get identical estimates as other packages.

Fields and Methods

Methods:
No methods defined.

Methods inherited from ProbeLevelModel:
calculateResidualSet, calculateWeights, fit, getAsteriskTags, getCalculateResidualsFunction, getChipEffectSet, getProbeAffinityFile, getResidualSet, getRootPath, getWeightsSet

Methods inherited from MultiArrayUnitModel:
getListOfPriors, setListOfPriors, validate

Methods inherited from UnitModel:
findUnitsTodo, getAsteriskTags, getFitSingleCellUnitFunction, getParameters

Methods inherited from Model:
as.character, fit, getAlias, getAsteriskTags, getDataSet, getFullName, getName, getPath, getRootPath, getTags, setAlias, setTags

Methods inherited from ParametersInterface:
getParameterSets, getParameters, getParametersAsString

Methods inherited from Object:
$, $<-, [[, [[<-, as.character, attach, attachLocally, clearCache, clearLookupCache, clone, detach, equals, extend, finalize, getEnvironment, getFieldModifier, getFieldModifiers, getFields, getInstantiationTime, getStaticInstance, hasField, hashCode, ll, load, names, objectSize, print, save, asThis

Model

For a single unit group, the averaging PLM of K probes is:

y_{ik} = \theta_i + \varepsilon_{ik}

where \theta_i are the chip effects for arrays i=1,...,I. The \varepsilon_{ik} are zero-mean noise with equal variance.

Different flavors of model fitting

The above model can be fitted in two ways, either robustly or non-robustly. Use argument flavor="mean" to fit the model non-robustly, i.e.

\hat{\theta}_{i} = 1/K \sum_k y_{ik}

.

Use argument flavor="median" to fit the model robustly, i.e.

\hat{\theta}_{i} = median_k y_{ik}

.

Missing values are always excluded.

Author(s)

Henrik Bengtsson

aroma.affymetrix documentation built on May 29, 2024, 4:32 a.m.