Preprocessing

Prepare raw microarray data for analysis

Process microarray data using background adjustment, normalization, and expression filtering. You can perform extensive preprocessing of Affymetrix^® and Illumina^® data and retrieve probe annotations from library files.

Functions

expand all

Robust Multi-Array Average Procedure

`affyrma`	Perform Robust Multi-array Average (RMA) procedure on Affymetrix microarray probe-level data
`affygcrma`	Perform GC Robust Multi-array Average (GCRMA) procedure on Affymetrix microarray probe-level data
`affyinvarsetnorm`	Perform rank invariant set normalization on probe intensities from multiple Affymetrix CEL or DAT files
`affyprobeaffinities`	Compute Affymetrix probe affinities from their sequences and MM probe intensities
`affysnpintensitysplit`	Split Affymetrix SNP probe intensity information for alleles A and B
`affysnpquartets`	Create table of SNP probe quartet results for Affymetrix probe set

Probe Set

`probesetvalues`	Create table of Affymetrix probe set intensity values
`probesetlookup`	Look up information for Affymetrix probe set
`probesetplot`	Plot Affymetrix probe set intensity values
`probelibraryinfo`	Create table of probe set library information

Background Adjustment

`rmabackadj`	Perform background adjustment on Affymetrix microarray probe-level data using Robust Multi-array Average (RMA) procedure
`rmasummary`	Calculate gene expression values from Affymetrix microarray probe-level data using Robust Multi-array Average (RMA) procedure
`gcrma`	Perform GC Robust Multi-array Average (GCRMA) background adjustment, quantile normalization, and median-polish summarization on Affymetrix microarray probe-level data
`gcrmabackadj`	Perform GC Robust Multi-array Average (GCRMA) background adjustment on Affymetrix microarray probe-level data using sequence information
`zonebackadj`	Perform background adjustment on Affymetrix microarray probe-level data using zone-based method

Normalization

`manorm`	Normalize microarray data
`quantilenorm`	Perform quantile normalization over multiple arrays
`mainvarsetnorm`	Perform rank invariant set normalization on gene expression values from two experimental conditions or phenotypes
`malowess`	Smooth microarray data using Lowess method
`exprprofrange`	Calculate range of gene expression profiles
`exprprofvar`	Calculate variance of gene expression profiles

Gene Filtering

`geneentropyfilter`	Remove genes with low entropy expression values
`genelowvalfilter`	Remove gene profiles with low absolute values
`generangefilter`	Remove gene profiles with small profile ranges
`genevarfilter`	Filter genes with small profile variance

Visualization

`maimage`	Spatial image for microarray data
`microplateplot`	Display visualization of microtiter plate
`ilmnbslookup`	Look up Illumina BeadStudio target (probe) sequence and annotation information
`magetfield`	Extract data from microarray structure

Featured Examples

Preprocessing Affymetrix Microarray Data at the Probe Level

Use MATLAB® and Bioinformatics Toolbox™ for preprocessing Affymetrix® oligonucleotide microarray probe-level data with two preprocessing techniques, Robust Multi-array Average (RMA) and GC Robust Multi-array Average (GCRMA).

Open Script