Linked Life Data

21429274

Source:http://linkedlifedata.com/resource/pubmed/id/21429274

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5-6
pubmed:dateCreated
2011-3-24
pubmed:abstractText
Many common human diseases and complex traits are highly heritable and influenced by multiple genetic and environmental factors. Although genome-wide association studies (GWAS) have successfully identified many disease-associated variants, these genetic variants explain only a small proportion of the heritability of most complex diseases. Genetic interactions (gene-gene and gene-environment) substantially contribute to complex traits and diseases and could be one of the main sources of the missing heritability. This paper provides an overview of the available statistical methods and related computer software for identifying genetic interactions in animal and plant experimental crosses and human genetic association studies. The main discussion falls under the three broad issues in statistical analysis of genetic interactions: the definition, detection and interpretation of genetic interactions. Recently developed methods based on modern techniques for high-dimensional data are reviewed, including penalized likelihood approaches and hierarchical models; the relationships between these methods are also discussed. I conclude this review by highlighting some areas of future research.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1469-5073
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
92
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
443-59
pubmed:dateRevised
2011-10-28
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Statistical analysis of genetic interactions.
pubmed:affiliation
Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA. TUnyi@ms.soph.uab.eduUT
pubmed:publicationType
Journal Article, Review, Research Support, N.I.H., Extramural