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What documentation exists for R?

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Chapter 5: R Add-On Packages 69<br />

annotate Associate experimental data in real time to biological metadata from web databases<br />

such as GenBank, LocusLink and PubMed. Process and store query<br />

results. Generate HTML reports of analyses.<br />

apComplex<br />

Estimate protein complex membership using AP-MS protein data.<br />

applera Tools <strong>for</strong> Applied Biosystems microarrays AB1700 data analysis and quality<br />

controls.<br />

arrayMagic<br />

Utilities <strong>for</strong> quality control and processing <strong>for</strong> two-color cDNA microarray data.<br />

arrayQuality<br />

Per<strong>for</strong>ming print-run and array level quality assessment.<br />

beadarray Quality control and low-level analysis of BeadArrays.<br />

bim Bayesian interval mapping diagnostics: functions to interpret QTLCart and<br />

Bmapqtl samples.<br />

bioDist A collection of software tools <strong>for</strong> calculating distance measures.<br />

biocViews Categorized views of R package repositories.<br />

biomaRt Interface to BioMart databases (e.g., Ensembl)<br />

bridge Bayesian Robust Inference <strong>for</strong> Differential Gene Expression.<br />

cellHTS Analysis of cell-based screens.<br />

cghMCR Find chromosome regions showing common gains/losses.<br />

clusterStab<br />

Compute cluster stability scores <strong>for</strong> microarray data.<br />

codelink Manipulation of Codelink Bioarrays data.<br />

convert Convert Microarray Data Objects.<br />

copa Functions to per<strong>for</strong>m cancer outlier profile analysis.<br />

ctc Tools to export and import Tree and Cluster to other programs.<br />

daMA Functions <strong>for</strong> the efficient design of factorial two-color microarray experiments<br />

and <strong>for</strong> the statistical analysis of factorial microarray data.<br />

diffGeneAnalysis<br />

Per<strong>for</strong>ms differential Gene expression Analysis.<br />

ecolitk Metadata and tools to work with E. coli.<br />

edd Expression density diagnostics: graphical methods and pattern recognition algorithms<br />

<strong>for</strong> distribution shape classification.<br />

exprExternal<br />

Implementation of exprSet using externalVectors.<br />

externalVector<br />

Basic class definitions and generics <strong>for</strong> external pointer based vector objects <strong>for</strong><br />

R.

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