Association of variations in I kappa B-epsilon with Graves' disease using

classical and myGrid methodologies

Peter Li

School of Computing ScienceUniversity of Newcastle upon Tyne

In silico experiments in bioinformatics

Bioinformatics analyses - in silico experiments - workflows

EMBL

BLAST

Clustal-W

Genscan

Resources/Services

Example workflow: Investigate the evolutionary relationships between proteins

Clustal-W

Proteinsequences

Multiplesequencealignment

Query

Issues in bioinformatics

Large amounts of distributed data in different databases

Highly heterogeneous

Lack of standards

Many applications

Different algorithms, implementations

Lack of programmatic access

Difficult to perform bioinformatics analyses

e-Science and myGrid

• e-Science for in silico experiments– Potential solution to problems in bioinformatics– Using the Grid as a framework– Bioinformatics resources deployed as Web Services

• myGrid– Development of middleware to support the

performance of in silico experiments in biology– Investigated the use of myGrid workflow technology in

the genetic analysis of Graves’ disease

Graves’ disease

• Autoimmune thyroid disease

• Lymphocytes attack thyroid gland cells causing hyperthyroidism

• An inherited disorder• Complex genetic basis• Symptoms:

– Increased pulse rate, sweating, heat intolerance

– goitre, exophthalmos

In silico experiments in Graves’ disease

• Microarray data analysis

• Gene annotation pipeline

• Design of genotype assays for SNP variations

Classical approach to the bioinformatics of Graves’ diseaseData Analysis - Microarray

Import microarray data to Affymetrix data Mining Tool, Run Analyses and select

Experiment Design to test Hypotheses Find restriction sites and design primers by eye for genotyping experiments

Study Annotations for many different Genes

Select Gene and Visually examine SNPS lying within

Taverna workflow system

• Used to compose and enact in silico experiments in myGrid

• Freefluo enactor• Scufl language• Workbench GUI

– Service browser– Model explorer for workflow

composition– Graphical view of workflow

• Free and open sourcehttp://taverna.sf.net

Modelling in silico experiments as workflows

• Semantic, syntactic and format typing of data in workflow

• Data has to be filtered, transformed, parsed for consumption by services

Annotation Pipeline

GO MEDLINE KEGG SwissProt InterPro PDB Blast HGBASE

Query

Results: Differential expression and variations of the I kappa B-epsilon gene

Mean NFKBIE expression levels -

• Controls: 1.60 +/- 0.11 (SEM)

• GD: 2.22 +/- 0.20 (SEM)

• P=0.0047 (T-test)

n=303’ UTR SNP – 3948 C/A

- Mnl restriction site- χ2 = 9.1, p = 0.0025, Odds Ratio = 1.4

Comparison between conventional bioinformatics and Taverna workflow approaches

• Advantages– Graphical composition of experiments– Automation and speed– Management of workflow information– Share and reuse workflows for other diseases

• Issues– Initial cost of learning/activation energy– Lack of Web Service interface to required

resources

Acknowledgements

• Institute of Human Genetics– Simon Pearce and Claire Jennings

• School of Computing Science– Anil Wipat, Matthew Pocock and Keith

Hayward

• European Bioinformatics Institute– Tom Oinn