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aroma.affymetrix (version 2.2.0)

LinearModelProbeSequenceNormalization: The LinearModelProbeSequenceNormalization class

Description

Package: aroma.affymetrix Class LinearModelProbeSequenceNormalization Object ~~| ~~+--AromaTransform ~~~~~~~| ~~~~~~~+--Transform ~~~~~~~~~~~~| ~~~~~~~~~~~~+--ProbeLevelTransform ~~~~~~~~~~~~~~~~~| ~~~~~~~~~~~~~~~~~+--ProbeLevelTransform3 ~~~~~~~~~~~~~~~~~~~~~~| ~~~~~~~~~~~~~~~~~~~~~~+--AbstractProbeSequenceNormalization ~~~~~~~~~~~~~~~~~~~~~~~~~~~| ~~~~~~~~~~~~~~~~~~~~~~~~~~~+--LinearModelProbeSequenceNormalization Directly known subclasses: BasePositionNormalization public abstract static class LinearModelProbeSequenceNormalization extends AbstractProbeSequenceNormalization This abstract class represents a normalization method that corrects for systematic effects in the probe intensities due to probe-sequence dependent effects that can be modelled using a linear model.

Usage

LinearModelProbeSequenceNormalization(...)

Arguments

...
Arguments passed to the constructor of AbstractProbeSequenceNormalization.

Fields and Methods

Methods: No methods defined. Methods inherited from AbstractProbeSequenceNormalization: fitOne, getAromaCellSequenceFile, getTargetFile, indexOfMissingSequences, predictOne, process Methods inherited from ProbeLevelTransform3: clearCache, getCellsTo, getCellsToFit, getCellsToUpdate, getUnitsTo, getUnitsToFit, getUnitsToUpdate, writeSignals Methods inherited from Transform: getOutputDataSet, getOutputDataSetOLD20090509, getOutputFiles Methods inherited from AromaTransform: getExpectedOutputFiles, getExpectedOutputFullnames, getFullName, getInputDataSet, getName, getOutputDataSet, getOutputDataSet0, getOutputFiles, getPath, getTags, isDone, process, setTags Methods inherited from Object: asThis, getChecksum, $, $<-, [[, [[<-, as.character, attach, attachLocally, clearCache, clearLookupCache, clone, detach, equals, extend, finalize, gc, getEnvironment, getFieldModifier, getFieldModifiers, getFields, getInstantiationTime, getStaticInstance, hasField, hashCode, ll, load, objectSize, print, registerFinalizer, save

Requirements

This class requires that an aroma probe sequence file is available for the chip type.

Memory usage

The model fitting methods of this class are bounded in memory. This is done by first building up the normal equations incrementally in chunks of cells. The generation of normal equations is otherwise the step that consumes the most memory. When the normal equations are available, the solve() method is used to solve the equations. Note that this algorithm is still exact.