Practical aspects of genome-wide association interaction analysis

Large-scale epistasis studies can give new clues to system-level genetic mechanisms and a better understanding of the underlying biology of human complex disease traits. Though many novel methods have been proposed to carry out such studies, so far only a few of them have demonstrated replicable res...

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Bibliographic Details
Published in:	Human genetics 2014-11, Vol.133 (11), p.1343-1358
Main Authors:	Gusareva, Elena S., Van Steen, Kristel
Format:	Article
Language:	eng
Subjects:	Algorithms Analysis Biomedical and Life Sciences Biomedicine Criminal investigation Epistasis, Genetic Gene Function Genetics & genetic processes Genome, Human - genetics Genome-Wide Association Study - methods Genome-Wide Association Study - standards Genomes Genomics Génétique & processus génétiques Human Genetics Humans Life sciences Meta-Analysis as Topic Metabolic Diseases Models, Genetic Molecular Medicine Review Paper Sciences du vivant
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Summary:	Large-scale epistasis studies can give new clues to system-level genetic mechanisms and a better understanding of the underlying biology of human complex disease traits. Though many novel methods have been proposed to carry out such studies, so far only a few of them have demonstrated replicable results. Here, we propose a minimal protocol for genome-wide association interaction (GWAI) analysis to identify gene–gene interactions from large-scale genomic data. The different steps of the developed protocol are discussed and motivated, and encompass interaction screening in a hypothesis-free and hypothesis-driven manner. In particular, we examine a wide range of aspects related to epistasis discovery in the context of complex traits in humans, hereby giving practical recommendations for data quality control, variant selection or prioritization strategies and analytic tools, replication and meta-analysis, biological validation of statistical findings and other related aspects. The minimal protocol provides guidelines and attention points for anyone involved in GWAI analysis and aims to enhance the biological relevance of GWAI findings. At the same time, the protocol improves a better assessment of strengths and weaknesses of published GWAI methodologies.
ISSN:	0340-6717 1432-1203 1432-1203