Premium
Do our “big data” in genetic analysis need to get bigger?
Author(s) -
Baker Laura A.
Publication year - 2014
Publication title -
psychophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.661
H-Index - 156
eISSN - 1469-8986
pISSN - 0048-5772
DOI - 10.1111/psyp.12351
Subject(s) - trait , relevance (law) , data science , psychology , research domain criteria , missing heritability problem , heritability , genome wide association study , sample (material) , psychopathology , biology , evolutionary biology , genetic variants , computer science , genetics , clinical psychology , gene , single nucleotide polymorphism , political science , genotype , law , programming language , chemistry , chromatography
Individual papers in this special issue might seem disappointing in their lack of discovery of specific genes of potential relevance to mental disorders. Yet, collectively, they yield information that could not be gleaned otherwise. Combining genome‐wide complex trait analysis and classic approaches to estimate heritability in the same sample, and supplementing genome‐wide association studies of common variants with exome and sequencing analyses, provides an unprecedented opportunity to examine major issues encountered in genetic research of complex traits, in ways not easily done with a series of unrelated studies using different samples, measures, and analytical approaches. Extending molecular genetic approaches to fully multivariate analyses will be an important future direction. These will require bigger analyses of even bigger big data, but will be essential in efforts to redefine psychopathology in the Research Domain Criteria (RDoC) approach promoted in the NIMH strategic plan.