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Related Experiment Video

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Infinium Assay for Large-scale SNP Genotyping Applications

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Published on: November 19, 2013

Shared Genomics: Developing an accessible integrated analysis platform for Genome-Wide Association Studies.

David Hoyle¹, Mark Delderfield, Lee Kitching

¹North-West Institute for BioHealth Informatics (NIBHI), University of Manchester, Manchester, UK.

Summit on Translational Bioinformatics

|February 25, 2011

Summary

Genome-wide association studies identify genomic locations linked to diseases. This work introduces an integrated Workbench for parallelized statistical genetics analysis and biological annotation, aiding clinical researchers.

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Area of Science:

Genetics
Bioinformatics
Computational Biology

Background:

Genome-wide association studies (GWAS) are increasingly utilized to detect genomic loci associated with various disease conditions.
The large scale of genomic data necessitates computationally and bioinformatically intensive analysis methods.

Purpose of the Study:

To present an integrated Workbench designed for clinical researchers.
To provide user-friendly access to parallelized statistical genetics analysis tools.
To biologically annotate statistical genetics results using existing bioinformatics workflows.

Main Methods:

Development of an integrated Workbench platform.
Integration of parallelized statistical genetics analysis codes.
Reuse of existing Taverna workflows for biological annotation of results.

Main Results:

The Workbench offers accessible parallelized analysis for large genomic datasets.
Biological annotation of statistical genetics findings is facilitated through reusable workflows.
The system supports clinical researchers in interpreting GWAS results.

Conclusions:

The integrated Workbench enhances the analysis of genome-wide association studies.
User-friendly access to advanced computational tools aids clinical research.
Combining statistical genetics with bioinformatics annotation improves disease gene discovery.