ontologies go

8/7/2019 Ontologies GO

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Sheena Scroggins

BI 7553

Fall 2010


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Ontologies

An ontology is a shared representation

of a subject area, in which terms andhierarchical relationships among them

are defined


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Gene Ontology Project

A collaboration between many

databases to ensure consistent

descriptions of gene products.

Started with Flybase, (Drosophila),

Saccharomyces Genome Database

(SGD) and Mouse Genome Database(MGD), but now includes many more


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GO Project Goals

Develop and maintain

vocabulary of gene and gene

product characteristics Annotate genes and gene products,

curate and publish data

Provide tools to facilitate access to alldata provided by the GO Project.


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GO-Vocabulary

Used to describe 3 characteristics of

proteins:

y Cellular component

y Biological Process

y Molecular Function

Protein or gene may participate in more

than one molecular function, biologicalprocess, and cellular component.


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GO-Vocabulary

Cellular Component

y

Describes locations of genes and proteins. Anatomical structures: ie cytoplasm or

nucleus

Gene product group: ie ribosome or ubiquitin

ligase complex


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GO-Vocabulary

Biological Process

y

The overall goal of the gene product Terms for broad processes: ie mitosis or

signal transduction

Terms for specific processes: ie pyrimidine

metabolic process


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GO-Vocabulary

Molecular Function

y The function of the gene products:

Terms for broad functions: ie catalytic activity

or hydrolase activity

Terms for more specific functions: ie Toll

receptor binding or protein-arginine deiminase

activity

Represent activities of proteins anddoes not specify where or when, or in

what context, the action takes place.


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GO-Vocabulary

Biological Process Molecular Function

A process must havemore than one distinct

step

Larger picture

description

Many molecular

functions have theword activity added to

them to help

distinguish from

biological process

Smaller picture

description


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GO Project

Develop and maintain vocabulary of

gene and gene product characteristics

Annotate genes and geneproducts, curate and publish

data

Provide tools to facilitate access to alldata provided by the GO Project.


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GO Annotation

Using GO terms to describe the

activities and localization of a gene

product, providing references and

indicating what evidence supports the

annotations


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GO Annotation

Includes gene product identifier, GO

terms, and the following data:

y The reference used to make the annotation

y An evidence code denoting the type of

evidence upon which the annotation is

basedy The date and the creator of the annotation


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GO Annotation

Experimental Evidence Codesy Cited paper displayed results from a

physical characterization of a gene or gene

product that supported the association of aGO term.

Inferred from Experiment (EXP)

Inferred from Direct Assay (IDA)

Inferred from Physical Interaction (IPI)

Inferred from Mutant Phenotype (IMP)

Inferred from Genetic Interaction (IGI)

Inferred from Expression Pattern (IEP)


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GO Annotation

ComputationalAnalysis Evidence Codesy Annotation based on an in silico analysis of the

gene sequence and/or other data as describedin the cited reference.

Inferred from Sequence or structural Similarity(ISS)

Inferred from Sequence Orthology (ISO)

Inferred from Sequence (ISA)

Inferred from Sequence Model (ISM) Inferred from Genomic Context (IGC)

inferred from Reviewed Computational Analysis(RCA)


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GO Annotation

Author Statement Evidence Codes

y

Annotation made on the basis of astatement made by the author(s) in the

reference cited.

Traceable Author Statement (TAS)

Non-traceable Author Statement (NAS)


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GO Annotation

Curatorial Statement Evidence Codes

y

Annotation made on the basis of a curatorialjudgment that does not fit into one of the

other evidence code classifications.

Inferred by Curator (IC)

No biological Data available (ND) evidence

code


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GO Project

Develop and maintain vocabulary of

gene and gene product characteristics

Annotate genes and gene products,

curate and publish data

Provide tools to facilitate

access to all data provided by

the GO Project.


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GO Tools

There are lots of tools for using the data

provided by the GO Project, including

online and downloadable versions.

The GO Consortium works directly with

two tools:


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AmiGo is the application used to searchthe Gene Ontology database.

Available online and as a download


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Search for a gene or gene product andview the GO term associations


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Gene Search in AmGO


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Perform a BLAST search and view theGO term associations for the genes or

proteins returned


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BLAST Results in AmiGO


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Other uses:

y Search for GO terms and view the genes or

gene products they are annotated to

y Browse the GO ontology and view terms

y Term enrichment tool is used to discover

what a set of genes may have in common by

examining annotations and finding

significant shared GO terms.


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An open source ontology editor developed and

maintained by the Gene Ontology Consortium. Features:

y Comprehensive search and filter interface

y Interface can be customized to user preferences.

y Reasoner tool that can infer links based on existingrelationships and their properties.

Can be used to view, search and edit anyontology, not just the Gene Ontology


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Viewing Ontologies in EDIT

OBO-Edit uses a graph-based approach for

ontology editing


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Default displays anontology in tree view.Each line in the treeview represents arelationship between

terms, with an arrowindicating the directionof the relationship.A term in the tree viewmay be expanded to

show its childrelationships

FIGURE 1-A

Day-Richter J, et al.

OBO-Edit - an ontology editor for biologists.

Bioinformatics 2007;23:2198-2200.


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The DAG Viewer

plugin displaysevery path from a

selected term to the

ontology root

FIGURE 1-A





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Editing Ontologies in

OBO-Edit presents structural ontology

editing operations, such as adding new

terms or new relationships, to the user

as graph editing operations.

All edits in OBO-Edit are tracked,

allowing users to undo any change they

make during an editing session.


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The Ontology Editor

serves as the editinginterface for adding

or removing terms

and relationships.

FIGURE 1-ADay-Richter J, et al.




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The Term Editor panel

allows users to editthe term name,

definition, synonyms

and other textual

metadata

FIGURE 1-B





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Searching & Filtering in

The search facility in OBO-Edit is built

around filters.

y Term attribute (such as name, definition)

y Comparison (equals, starts with, is less than,

etc.)

y Value.

Compound filters combine a number offilters together using the Boolean

operators AND and OR.


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Criteria

specified in the

filter interface

can be used tosearch for an

ontology.

FIGURE 1-C Day-Richter J, et al.




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GO Review

Provide vocabulary for gene and gene

product descriptions, annotations and

tools.

AmiGO- Application used to search

the GO databases

OBO-Edit- Application to view

and edit ontologies, including the GeneOntology

http://www.geneontology.org/


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What GO Is Not

GO is not a database of gene sequences, nor acatalog of gene products.

GO describes how gene products behave in acellular context.

Database lists attributes of genes and geneproducts, not the genes or products themselves.y e.g. cytochrome c is not in the ontologies, but attributes of

cytochrome c, such as oxidoreductase activity, are.

Processes, functions or components that areunique to mutants or diseases are not includedy e.g. oncogenesis is not a valid GO term because causing

cancer is not the normal function of any gene.


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What GO Is Not

Also not included:

y Attributes of sequence such as intron/exon

parameters

y Protein domains or structural features

y Protein-protein interactions.

y Environment, evolution and expression.

y

Anatomical or histological features abovethe level of cellular components, including

cell types.


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References

http://www.geneontology.org/

http://wiki.geneontology.org/index.php/AmiGO_Manual:_Overview

http://oboedit.org/docs/index.htm Pevsner, J. Bioinformatics and

Functional Genomics, 2009. Chp 10


OBO-Edit - anontology editor for biologists.Bioinformatics 2007;23:2198-2200.

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