I study computational and quantitative biology with a focus on network aging. This site is to serve as my note-book and to effectively communicate with my students and collaborators. Every now and then, a blog may be of interests to other researchers or teachers. Views in this blog are my own. All rights of research results and findings on this blog are reserved. See also http://youtube.com/c/hongqin
Friday, July 17, 2015
GWA, genome partition on missing heritability
http://www.ncbi.nlm.nih.gov/pubmed/26179597 cites 'genome partition' as a alternative way to look at GWA and missing heritability: One way forward in addressing this issue is to compare results obtained from GWA with emerging
“genome partitioning” methods based on quantitative genetics. These approaches do not identify individual SNPs or haplotypes, rather than linkage groups of SNPs (usually chromosomes) that together explain more phenotypic variance than expected from a polygenic null model where all markers contribute equally (Yang et al. , 2011b,a; Hill, 2012). Genome partitioning has proven extremely useful for retrieving some of the missing heritability unaccounted for by genotypic variants identified through GWA. This has been well illustrated in complex phenotypes, for example in human height (Yang et al. , 2010, 2011b) and disorders such as schizophrenia, Tourette syndrome and obsessive-compulsive disorder (Lee et al. , 2012; Davis et al. , 2013).
Yang J, Benyamin B,McEvoy BP et al. (2010) Common SNPs explain a large proportion of the heritability for human height. Nature Genetics , 42 , 565–569.
Yang J, Lee SH, Goddard ME, Visscher PM (2011a) GCTA: a tool for genome-wide complex trait analysis. The American Journal of Human Genetics , 88 , 76–82.
Yang J, Manolio TA, Pasquale LR et al. (2011b) Genome partitioning of genetic variation for complextraits using common SNPs. Nature Genetics , 43 , 519–525.