Overview of Bioconductor

Aedín Culhane

aedin@jimmy.harvard.edu

http://bcb.dfci.harvard.edu/~aedin

http://www.hsph.harvard.edu/research/aedin-culhane

BioconductorBiannual 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).

– LATEX 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 interestopenVignette()

S4 classes and ExpressionSet

• Within Bioconductor, you will encounter packages are structured around S4 object-oriented 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

Aedín 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/BiocViews.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 OverviewA 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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ExpressionSet Class in R

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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

R Code

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More on GEOquery

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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))

Affy SNP Arrays

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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/

oligo-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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