Ontology application and use at the encode dcc

Ontology application and use at the ENCODE DCC

Venkat MalladiData Wrangler, ENCODE DCC Department of Genetics Stanford University School of Medicine

Venkat Malladi ENCODE DCC

Overview


MetadataModel

Ontologies Search Futuredirections

Intro to ENCODE and the DCC

What is ENCODE?

Venkat Malladi ENCODE DCC Modified from PLoS Biol 9-e1001046,2011

(M. Pazin)

Approximately ~30 different assays

Role of the Data Coordination Center


Production labsAnalysis groups

Genome Browser

ENCODE portal(DCC)

Data files

Metadata DCCDCC Integrative websites

Scientificcommunity

Role: Data generation Data organization Data access

Tasks: Perform assays Data processing & validation Web-based searchesPerform analyses Data file storage Data

downloadsValidate data Metadata curation

Submit data filesSubmit metadata

Challenge: Find common biosamples from data generated by two consortia


356 termshttp://encodeproject.org/ENCODE/cellTypes.html

Projects are internally consistent…..

314 termsGEO characteristics: common_name, tissue_type, cell_type, lines

Simple text match


360 termsCell type

… but only 3 biosample names match exactly between projects

314 termsGEO

IMR90PBMCTh17

Metadata annotation using Ontologies

An ontology is a set of words and relationships … … All relationships must be true.


nucleuschromosome

mitochondrial chromosome

mitochondrion

cellParent term

Child term

part_of

part_of

part_of

part_of is_a

part_ofX

An ontology is a set of words and relationships.Need true relationships because inferences can be based

upon them.


nucleuschromosome

mitochondrial chromosome

mitochondrion

cellParent term

Child term

part_of

part_of

part_of

part_of is_a

part_ofX

part_of

X part_of

http://www.geneontology.org/GO.ontology.relations.shtml

True

False

Why use ontologies?


Reason 1: Consistent way of describing biological concepts

Reason 2: Consistency of language facilitates identification of related data easily.

Reason 3: Consistency in data analysis because relationships between terms provide flexibility of grouping while everyone uses the same set of metadata

What metadata is annotated with ontologies?


1. the biological sample serving as input (Biosample)

2. the reagents and conditions applied to the biological input (Treatment)

3. the set of methods and conditions to survey the biological input (Assay)

Biosample ontologies


1. Uber anatomy ontology (Uberon) - structure, location and heterogenous mixture of cells

2. Cell Ontology (CL) - primary cells or stem cells

3. Experimental Factor Ontology (EFO) - no direct corresponding anatomical structure or physiological cell type

Challenge: Find all heart-related tissues?


Heart_OCHCFHCFaaHCMOthers?

Fetal HeartHeartRight AtriumRight VentricleOthers?

Searching ENCODE metadata


Ontology driven search


Future directions


• Additional ontologies

• Ontology- based data validations

Additional ontologies


• Protein Ontology (PRO,http://pir.georgetown.edu/pro/pro.shtml)o transforming growth factor beta-1 (human)— PR:P01137

• EDAM Ontology (EDAM, http://edamontology.org)o FASTQ—format:1930, BAM—format:2572o sequence alignment—data:0863

http://pir.georgetown.edu/pro/pro.shtml

http://edamontology.org/

Ontology based validations


Acknowledgments


Nikhil Podduturi, Laurence Rowe, Forrest Tanaka

Esther Chan, Jean Davidson, Venkat Malladi, Cricket Sloan, J. Seth Strattan

Eurie Hong, Mike Cherry (PI), Jim Kent (co-PI), Ben Hitz

Brian Lee, Stuart Miyasato, Matt Simison, Zhenhua Wang, Marcus Ho

Data Wranglers

Software Engineers

QA, administration, biocuration

National Institute of General Medical Sciences of the United States AQ1215 National Institutes of Health (GM10331601); U41 grant from National Human Genome Research Institute at the U.S. National Institutes of Health (HG006992)

Ontology application and use at the encode dcc

Science

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