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Title: Estimation of SNP Heritability from Dense Genotype Data
Contributor(s): Lee, Sang Hong  (author); Yang, Jian (author); Wray, Naomi R (author); Chen, Guo-Bo (author); Ripke, Stephan (author); Stahl, Eli A (author); Hultman, Christina M (author); Sklar, Pamela (author); Visscher, Peter M (author); Sullivan, Patrick F (author); Goddard, Michael E (author)
Publication Date: 2013
Open Access: Yes
DOI: 10.1016/j.ajhg.2013.10.015Open Access Link
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Abstract: To the Editor: Recently, Speed et al. undertook a comprehensive and elegant evaluation of five key assumptions underlying the linear mixed model implemented in the program GCTA for estimation of SNP heritability. They concluded that the method is robust to violations of four of the assumptions. However, they found that SNP-heritability estimates were sensitive to uneven linkage disequilibrium (LD) between SNPs (implying uneven tagging of causal variants) and suggested an approach to improving the robustness of estimates in this context.
Publication Type: Journal Article
Source of Publication: American Journal of Human Genetics, 93(6), p. 1151-1155
Publisher: Cell Press
Place of Publication: Houston, United States of America
ISSN: 1537-6605
Fields of Research (FoR) 2008: 060405 Gene Expression (incl. Microarray and other genome-wide approaches)
Fields of Research (FoR) 2020: 310505 Gene expression (incl. microarray and other genome-wide approaches)
Socio-Economic Objective (SEO) 2008: 920110 Inherited Diseases (incl. Gene Therapy)
Socio-Economic Objective (SEO) 2020: 200101 Diagnosis of human diseases and conditions
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article

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