In an attempt to discover and unravel genetic predisposition to complex traits, new statistical methods have emerged that utilize multiple sources of data. This appeal to data aggregation is seen on various levels: across genetic variants, across genomic/biological/environmental measures and across different studies, often with fundamentally differing designs. While combining data can increase power to detect genetic variants associated with disease phenotypes, care must be taken in the design, analysis, and interpretation of such studies. Here, we explore methodologies employed to combine sources of genetic data and discuss the prospects for novel advances in the fields of statistical genetics and genetic epidemiology.
Investigators
Abbreviation
J Biom Biostat
Publication Date
2013-06-01
Volume
4
Issue
3
Page Numbers
1000166
Pubmed ID
24009987
Medium
Print
Full Title
Statistical Approaches to Combine Genetic Association Data.