Linkage disequilibrium score regression: Difference between revisions
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In statistical genetics, linkage disequilibrium score regression (abbreviated LDSC)[1] is a technique that aims to quantify the separate contributions of polygenic effects and various confounding factors, such as population stratification, based on summary statistics from genome-wide association studies (GWASs). The approach involves using regression analysis to examine the relationship between linkage disequilibrium scores and the test statistics of the single-nucleotide polymorphisms (SNPs) from the GWAS. Here, the "linkage disequilibrium score" for a SNP "is the sum of LD r2 measured with all other SNPs".[2] LDSC can be used to produce SNP-based heritability estimates, to partition this heritability into separate categories, and to calculate genetic correlations between separate phenotypes. Because the LDSC approach relies only on summary statistics from an entire GWAS, it can be used efficiently even with very large sample sizes.[3] LDSC can also be applied across traits to estimate genetic correlations. This extension of LDSC, known as cross-trait LD score regression, has the advantage of not being biased if used on overlapping samples.[4] There is also another extension of LDSC, known as stratified LD score regression, that takes into account genetic linkage between markers.[5]
References
- ^ Ni, Guiyan; Moser, Gerhard; Wray, Naomi R.; Lee, S. Hong; Ripke, Stephan; Neale, Benjamin M.; Corvin, Aiden; Walters, James T.R.; Farh, Kai-How (June 2018). "Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood". The American Journal of Human Genetics. 102 (6): 1185–1194. doi:10.1016/j.ajhg.2018.03.021. ISSN 0002-9297. PMC 5993419. PMID 29754766.
{{cite journal}}: CS1 maint: PMC format (link) - ^ Neale, Benjamin M.; Price, Alkes L.; Daly, Mark J.; Patterson, Nick; Consortium, Schizophrenia Working Group of the Psychiatric Genomics; Yang, Jian; Ripke, Stephan; Finucane, Hilary K.; Loh, Po-Ru (March 2015). "LD Score regression distinguishes confounding from polygenicity in genome-wide association studies". Nature Genetics. 47 (3): 291–295. doi:10.1038/ng.3211. ISSN 1546-1718. PMC 4495769. PMID 25642630.
{{cite journal}}: CS1 maint: PMC format (link) - ^ Neale, Benjamin M.; Evans, David M.; Gaunt, Tom R.; Paternoster, Lavinia; Anttila, Verneri; Bulik-Sullivan, Brendan K.; Price, Alkes L.; Finucane, Hilary K.; Warrington, Nicole M. (2017-01-15). "LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis". Bioinformatics. 33 (2): 272–279. doi:10.1093/bioinformatics/btw613. ISSN 1367-4803. PMC 5542030. PMID 27663502.
{{cite journal}}: CS1 maint: PMC format (link) - ^ Neale, Benjamin M.; Price, Alkes L.; Daly, Mark J.; Robinson, Elise B.; Patterson, Nick; Perry, John R. B.; Duncan, Laramie; Consortium 3, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control; Consortium, Psychiatric Genomics (November 2015). "An atlas of genetic correlations across human diseases and traits". Nature Genetics. 47 (11): 1236–1241. doi:10.1038/ng.3406. ISSN 1546-1718. PMC 4797329. PMID 26414676.
{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: numeric names: authors list (link) - ^ Price, Alkes L.; Neale, Benjamin M.; Patterson, Nick; Daly, Mark J.; Raychaudhuri, Soumya; Okada, Yukinori; Perry, John R. B.; Lindstrom, Sara; Stahl, Eli (2015-11). "Partitioning heritability by functional annotation using genome-wide association summary statistics". Nature Genetics. 47 (11): 1228–1235. doi:10.1038/ng.3404. ISSN 1546-1718. PMC 4626285. PMID 26414678.
{{cite journal}}: Check date values in:|date=(help)CS1 maint: PMC format (link)
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