Overview of Bioconductor

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

2. 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()

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

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

5. 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

6. 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.orgwww.r-bloggers.com

7. 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 interest openVignette()

8. 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)

9. 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")

10. Example: 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 library(ALL) data(ALL) slotNames(ALL) ALL@phenoData phenoData(ALL) class(ALL) ?ExpressionSet

11. 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

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

13. 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

14. Some common data types • Microarray • SNP • NGS

15. A Microarray Overview

16. Reading Affymetrix Data library(affy) require(affy) # Alternative affybatch <- ReadAffy(celfile.path="[Location of your data]") eSet<-justRMA()

17. Sample R code

18. ExpressionSet Class in R

19. Assessing Data Quality

20. Public Microarray Data ArrayExpress 21997 Studies (622,617 profiles,) GEO 22,735 Studies (558,074 profiles) Statistics May 2011

21. R Code

22. 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))

23. Affy SNP Arrays

24. Process – Affy SNP Arrays (Oligo package)

25. Other Arrays • Illumina • Lumi package • 2 color spotted arrays • Limma package • Other arrays • http://www.bioconductor.org/help/workflows/oligo-arrays/

26. Next Generation Sequencing Data

27. R Code

28. 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

29. R basics: Getting help • To get help • ?mean • help(mean) • help.search(“mean”)‏ • apropos("mean") • example(mean)‏ • http://www.bioconductor.org/help/

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