Overview of Bioconductor
Aed ín Culhane aedin@jimmy.harvard.edu
http://bcb.dfci.harvard.edu/~aedin http://www.hsph.harvard.edu/research/aedin-culhane

Bioconductor
Biannual release (normally April, October) to coincide with R release.
Current: Bioconductor 2.9
(release coincide with R 2.14)
To install use script on Bioconductor Website source("http://www.bioconductor.org/biocLite.R") biocLite()

Packages Overview
BioConductor web site
• Bioconductor BiocViews Task view
Software
Annotation Data
Experimental Data

What Packages do I need?
Specific to you data and analysis pipeline but for examples:
• Bioconductor Workshops
• Bioconductor Workflows

Main types of Annotation Packages
• Gene centric AnnotationDbi packages:
– Organism: org.Mm.eg.db.
– Technology/Platform: hgu133plus2.db.
– GeneSets and Pathway (biology level): GO.db or KEGG.db
– .db packages can be queried with sql or accessed using annotation package (totable, get, mget)
• Genome centric GenomicFeatures packages:
– Transriptome level: TxDb.Hsapiens.UCSC.hg19.knownGene
– Generic features: Can generate via GenomicFeatures
• biomaRt:
– Query web-based `biomart' resource for genes, sequence,
SNPs, and etc .
• See http://www.bioconductor.org/help/course-materials/2011/BioC2011/LabStuff/AnnotationSlidesBioc2011.pdf

Bioconductor resources
• Mailing List (sign up for daily digest)
• Documentation, workshop/course material online
– Slides from talks, pdf of tutorials, R code
• Help available for each software package
– Each package MUST contain vignette (howto)
• Other resources ww.Rseek.org www.r-bloggers.com

Vignette
• Tutorials, provide worked example of package
• Required in Bioconductor packages
• Written in Sweave (Leisch, 2002).
– L A T
E
X dynamic reports in which R code is embedded and executable
– All R code in vignette is checked (and executed) by R
CMD check
– http://www.bioconductor.org/docs/vignettes.html
library("Biobase") library("GOstats") # Load package of interest openVignette()

S4 classes and ExpressionSet
• Within Bioconductor, you will encounter packages are structured around S4 objectoriented programming proposed by John
Chambers (developer of S)
• A class provides a software abstraction of a real world object.
• A method performs an action on a class
(Think of a class as a noun, and method as verb)

Object (S4)
• An object is an instance of a class.
• Descriptions are stored in slots
• slotNames(ob1) lists all slots in object, or use str().
• To access slots
– ob1@slotname
– slotname(ob1), or
– slot(ob1, “slotname")

Example: ExpressionSet library(ALL) data(ALL) slotNames(ALL)
ALL@phenoData phenoData(ALL) class(ALL)
?ExpressionSet
> ALL
ExpressionSet (storageMode: lockedEnvironment) assayData: 12625 features, 128 samples element names: exprs protocolData: none phenoData sampleNames: 01005 01010 ... LAL4 (128 total) varLabels: cod diagnosis ... date last seen
(21 total) varMetadata: labelDescription featureData: none experimentData: use 'experimentData(object)' pubMedIds: 14684422 16243790
Annotation: hgu95av2

Method which act on a S4 class showMethods(class= "ExpressionSet") getMethod("write.exprs", "ExpressionSet")
Or if you wish to see how the package really works, download and look the source code

Getting Data into R &
Bioconductor
Aed ín Culhane aedin@jimmy.harvard.edu
http://www.hsph.harvard.edu/research/aedin-culhane/

Simple Excel SpreadSheet data
• Simple table
– read.table()
– read.csv()
– scan()
• However more datatype specialized. See Technologies on BiocViews.
– http://www.bioconductor.org/packages/release/BiocVi ews.html
• Large data files. Also see http://www.revolutionanalytics.com
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Some common data types
• Microarray
• SNP
• NGS
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A Microarray Overview
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Reading Affymetrix Data library(affy) require(affy) # Alternative affybatch <- ReadAffy(celfile.path="[Location of your data]") eSet<-justRMA()
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Sample R code
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May 2011
ExpressionSet Class in R
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May 2011
Assessing Data Quality
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Public Microarray Data
ArrayExpress
• 21997 Studies (622,617 profiles,)
GEO
• 22,735 Studies (558,074 profiles)
Statistics May 2011

May 2011
R Code
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May 2011
More on GEOquery require(GEOquery)
Let's try to load the GDS810 dataset which contains data on
Alzheimer's disease at various stages of severity.
GDS810<-getGEO("GDS810")
The getGEO function returns an object of class GEOData . You can get a description of this class like this: help("GEOData-class")
Meta(GDS810)
Columns(GDS810) head(Table(GDS810))
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May 2011
Affy SNP Arrays
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May 2011
Process – Affy SNP Arrays
(Oligo package)
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Other Arrays
• Illumina
– Lumi package
• 2 color spotted arrays
– Limma package
• Other arrays
– http://www.bioconductor.org/help/workflows/ol igo-arrays/
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Next Generation Sequencing
Data

R Code
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Exercise
• Install the library GEOquery
• Download the dataset GSE1297 using getGEO
• This data will be downloaded as an eSet, so to see the expression data and phenoData, use pData and exprs
• Use ArrayQualityMetrics to Assess the data quality of these data
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R basics: Getting help
• To get help
– ?mean
– help(mean)
• help.search(“mean”)
• apropos("mean")
• example(mean)
• http://www.bioconductor.org/help/

• With thanks to
• www.bioconductor.org/help/course.../Bioconductor-Introduction-lab.pdf
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