Using Bioconductor for Annotation

Bioconductor has extensive facilities for mapping between microarray probe, gene, pathway, gene ontology, homology and other annotations.

Bioconductor has built-in representations of GO, KEGG, vendor, and other annotations, and can easily access NCBI, Biomart, UCSC, and other sources.

• Sample Workflow
• Installation and Use
• Exploring Package Content
• Annotation Resources

Sample Workflow

The following psuedo-code illustrates a typical R / Bioconductor session. It continues the differential expression workflow, taking a 'top table' of differentially expressed probesets and discovering the genes probed, and the Gene Ontology pathways to which they belong.

## Affymetrix U133 2.0 array IDs of interest; these might be
## obtained from
##
##   tbl <- topTable(efit, coef=2)
##   ids <- tbl[["ID"]]
##
## as part of a more extensive workflow.
> ids <- c("39730_at", "1635_at", "1674_at", "40504_at", "40202_at")

## load libraries as sources of annotation
> library("hgu95av2.db")

## To list the kinds of things that can be retrieved, use the cols method.
> cols(hgu95av2.db)

## To list the kinds of things that can be used as keys 
## use the keytypes method
> keytypes(hgu95av2.db)

## To extract viable keys of a particular kind, use the keys method.
> head(keys(hgu95av2.db, keytype="ENTREZID"))

## the select method allows you to mao probe ids to ENTREZ gene ids...
> select(hgu95av2.db, ids, "ENTREZID", "PROBEID")
   PROBEID ENTREZID
1 39730_at       25
2  1635_at       25
3  1674_at     7525
4 40504_at     5445
5 40202_at      687

## ... and to GENENAME etc.
> select(hgu95av2.db, ids, c("ENTREZID","GENENAME"), "PROBEID")
   PROBEID ENTREZID                                           GENENAME
1 39730_at       25     c-abl oncogene 1, non-receptor tyrosine kinase
2  1635_at       25     c-abl oncogene 1, non-receptor tyrosine kinase
3  1674_at     7525 v-yes-1 Yamaguchi sarcoma viral oncogene homolog 1
4 40504_at     5445                                      paraoxonase 2
5 40202_at      687                              Kruppel-like factor 9

## find and extract the GO ids associated with the first id
> res <- select(hgu95av2.db, ids[1], "GO", "PROBEID")
> head(res)
   PROBEID         GO EVIDENCE ONTOLOGY
1 39730_at GO:0000115      TAS       BP
2 39730_at GO:0000287      IDA       MF
3 39730_at GO:0003677      NAS       MF
4 39730_at GO:0003785      TAS       MF
5 39730_at GO:0004515      TAS       MF
6 39730_at GO:0004713      IDA       MF

## use GO.db to find the Terms associated with those GOIDs
> library("GO.db")
> head(select(GO.db, res$GO, "TERM", "GOID"))
        GOID                                                                   TERM
1 GO:0000115  regulation of transcription involved in S phase of mitotic cell cycle
2 GO:0000287                                                  magnesium ion binding
3 GO:0003677                                                            DNA binding
4 GO:0003785                                                  actin monomer binding
5 GO:0004515                     nicotinate-nucleotide adenylyltransferase activity
6 GO:0004713                                       protein tyrosine kinase activity

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Installation and Use

Follow installation instructions to start using these packages. To install the annotations associated with the Affymetrix Human Genome U95 V 2.0, and with Gene Ontology, use

> source("http://bioconductor.org/biocLite.R")
> biocLite(c("hgu95av2.db", "GO.db"))

Package installation is required only once per R installation. View a full list of available software and annotation packages.

To use the AnnotationDbi and GO.db package, evaluate the commands

> library(AnnotationDbi")
> library("GO.db")

These commands are required once in each R session.

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Exploring Package Content

Packages have extensive help pages, and include vignettes highlighting common use cases. The help pages and vignettes are available from within R. After loading a package, use syntax like

> help(package="GO.db")
> ?select

to obtain an overview of help on the GO.db package, and the select method. The AnnotationDbi package is used by most .db packages. View the vignettes in the AnnotationDbi package with

> browseVignettes(package="AnnotationDbi")

To view vignettes (providing a more comprehensive introduction to package functionality) in the AnnotationDbi package. Use

> help.start()

To open a web page containing comprehensive help resources.

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Annotation Resources

The following guides the user through key annotation packages. Users interested in how to create custom chip packages should see the vignettes in the AnnotationForge package. There is additional information in the AnnotationDbi, OrganismDbi and GenomicFeatures packages for how to use some of the extra tools provided. You can also refer to the complete list of annotation packages.

Key Packages

• AnnotationDbi Almost all annotations require the AnnotationDbi package. This package will be automatically installed for you if you install another ".db" annotation package using biocLite(). It contains the code to allow annotation mapping objects to be made and manipulated as well as code to use the select methods etc..
• OrganismDbi\\ OrganismDbi allows meta packages that enable the user to access resources from several different packages as if they were coming from one place. So for example the Homo.sapiens package is enabled by OrganismDbi and allows the user to get access to GO.db, the associated organism package IDs and the related transcript data for the hg19 build of the human genome all as if it were contained in a single convenient object.
• GenomicFeatures GenomicFeatures allows the existance of TranscriptDb objects and allows convenient representation of ranges from Transcritomes. There are accessors for things like exons, transcripts as well as the select method for retrieving data from packages supported by GenomicFeatures.
• AnnotationForge AnnotationForge documents and assists in the creation of some kinds of custom annotation packages.
• Category This is the base level package for dealing with annotation questions that involve categorical data.
• GOstats This builds on what is found in Category so that you can do hypergeometric testing using the Gene Ontology found in the GO.db package.
• annotate This package contains many helpful tools for making use of annotations.
• biomaRt This package is a great way to pull annotation data directly from web based annotation resources. Such data is extremely "current", so it is a good idea to save and locally manage the data that you pull down from biomaRt so that your code will be reproducible.

Types of Annotation Packages

• Organism annotation packages contain all the gene based data for an entire organism. All Organism packages are named like this: org."Xx"."yy".db. Where "Xx" is the abbreviation for Genus and species. And "yy" is the source of the central ID that is used to tie all the data together. Some examples are: org.Hs.eg.db which is for Homo sapiens and is based upon Entrez Gene IDs. And org.At.tair.db which is for Arabidopsis thaliana and is based on the tair IDs.
• TransriptDb packages contain range and chromosome information for specific transcriptomes. These are based on a particular genome build and are are the place to look for where a gene/transcripts/exon coordinate information is relative to a genome. These are also named in a way that tells you about where the data came from and can be generated with functions contained in the GenomicFeatures package.
• OrganismDb packages are named for the species they represent (such as the Homo.sapiens package). These packages contain references to other key annotations packages and can thus represent all the underlying data as if it were coming from one place. So for example, the Homo.sapiens package can allow you to retrieve data about the ranges of a genes transcripts at the same time that you extract it's gene name because it represents both a the transcriptome and the relevant org package for Homo sapiens. These can be generated using functions in the OrganismDbi package if you have specific packages that you want to link together.
• There are also packages for questions about general systems biology data. Some examples of this are: KEGG.db for accessing data that pertains to Kyoto Encyclopedia of Genes and Genomes. GO.db for accessing data that pertains to the Gene Ontology. PFAM.db for accessing data that pertains to different protein family identifiers and how they relate to each other.
• Chip annotation packages are for accessing only the data from one specific platform at a time. These packages are named like this: "platformName".db. Where "platformName" is the name of the chip platform that these packages refer to. And example would be hgu95av2.db which is for the hgu95av2 platform from Affymetrix.
• Inparanoid homology packages are for accessing inparanoid data. hom."Xx".inp.db Where "Xx" is the abbreviation for Genus and species. An example is hom.Hs.inp.db which contains inparanoid based mapping data between genes for Homo sapiens and 35 other organisms.
• .db0 packages are for making custom platform specific packages. These packages are named like this: "name".db0. Where "name" is the name of the organism being represented. A list of the available .db0 packages can be obtained by calling available.db0Pkgs(). There is one of these for each supported organism. An example would be human.db0. Users should not need these installed unless they plan to make custom chip packages according the guidelines in the SQLForge vignette that is included with the AnnotationDbi package. These packages must be upgraded before you attempt to update your custom chip packages as they contain the source databases needed by the SQLForge code.
• For relevant Affymetrix platforms you may also want the cdf and probe packages for that platform. These packages are named using the following convention: "platformName"cdf and "platformName"probe. Where "platformName" is the name of the chip platform that these packages refer to.

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