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In [[statistical genetics]], '''linkage disequilibrium score regression''' (abbreviated '''LDSC''')<ref>{{Cite journal |last=Ni |first=Guiyan |last2=Moser |first2=Gerhard |last3=Wray |first3=Naomi R. |last4=Lee |first4=S. Hong |last5=Ripke |first5=Stephan |last6=Neale |first6=Benjamin M. |last7=Corvin |first7=Aiden |last8=Walters |first8=James T.R. |last9=Farh |first9=Kai-How |date=June 2018 |title=Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood |url=https://linkinghub.elsevier.com/retrieve/pii/S0002929718301101 |journal=The American Journal of Human Genetics |volume=102 |issue=6 |pages=1185–1194 |doi=10.1016/j.ajhg.2018.03.021 |issn=0002-9297 |pmc=PMC5993419 |pmid=29754766}}</ref> 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 statistic]]s of the [[single-nucleotide polymorphism]]s (SNPs) from the GWAS. Here, the "linkage disequilibrium score" for a SNP "is the sum of LD r<sup>2</sup> measured with all other SNPs".<ref>{{Cite journal |last=Neale |first=Benjamin M. |last2=Price |first2=Alkes L. |last3=Daly |first3=Mark J. |last4=Patterson |first4=Nick |last5=Consortium |first5=Schizophrenia Working Group of the Psychiatric Genomics |last6=Yang |first6=Jian |last7=Ripke |first7=Stephan |last8=Finucane |first8=Hilary K. |last9=Loh |first9=Po-Ru |date=March 2015 |title=LD Score regression distinguishes confounding from polygenicity in genome-wide association studies |url=https://www.nature.com/articles/ng.3211 |journal=Nature Genetics |language=en |volume=47 |issue=3 |pages=291–295 |doi=10.1038/ng.3211 |issn=1546-1718 |pmc=PMC4495769 |pmid=25642630}}</ref> LDSC can be used to produce SNP-based [[heritability]] estimates, to partition this heritability into separate categories, and to calculate [[genetic correlation]]s between separate [[phenotype]]s. Because the LDSC approach relies only on summary statistics from an entire GWAS, it can be used efficiently even with very large sample sizes.<ref>{{Cite journal |last=Neale |first=Benjamin M. |last2=Evans |first2=David M. |last3=Gaunt |first3=Tom R. |last4=Paternoster |first4=Lavinia |last5=Anttila |first5=Verneri |last6=Bulik-Sullivan |first6=Brendan K. |last7=Price |first7=Alkes L. |last8=Finucane |first8=Hilary K. |last9=Warrington |first9=Nicole M. |date=2017-01-15 |title=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 |url=https://academic.oup.com/bioinformatics/article/33/2/272/2525718 |journal=Bioinformatics |language=en |volume=33 |issue=2 |pages=272–279 |doi=10.1093/bioinformatics/btw613 |issn=1367-4803 |pmc=PMC5542030 |pmid=27663502}}</ref> 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.<ref>{{Cite journal |last=Neale |first=Benjamin M. |last2=Price |first2=Alkes L. |last3=Daly |first3=Mark J. |last4=Robinson |first4=Elise B. |last5=Patterson |first5=Nick |last6=Perry |first6=John R. B. |last7=Duncan |first7=Laramie |last8=Consortium 3 |first8=Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control |last9=Consortium |first9=Psychiatric Genomics |date=November 2015 |title=An atlas of genetic correlations across human diseases and traits |url=https://www.nature.com/articles/ng.3406 |journal=Nature Genetics |language=en |volume=47 |issue=11 |pages=1236–1241 |doi=10.1038/ng.3406 |issn=1546-1718 |pmc=PMC4797329 |pmid=26414676}}</ref> There is also another extension of LDSC, known as stratified LD score regression, that takes into account [[genetic linkage]] between markers.<ref>{{Cite journal |last=Price |first=Alkes L. |last2=Neale |first2=Benjamin M. |last3=Patterson |first3=Nick |last4=Daly |first4=Mark J. |last5=Raychaudhuri |first5=Soumya |last6=Okada |first6=Yukinori |last7=Perry |first7=John R. B. |last8=Lindstrom |first8=Sara |last9=Stahl |first9=Eli |date=2015-11 |title=Partitioning heritability by functional annotation using genome-wide association summary statistics |url=https://www.nature.com/articles/ng.3404 |journal=Nature Genetics |language=en |volume=47 |issue=11 |pages=1228–1235 |doi=10.1038/ng.3404 |issn=1546-1718 |pmc=PMC4626285 |pmid=26414678}}</ref>
In [[statistical genetics]], '''linkage disequilibrium score regression''' (abbreviated '''LDSC''')<ref>{{Cite journal |last=Ni |first=Guiyan |last2=Moser |first2=Gerhard |last3=Wray |first3=Naomi R. |last4=Lee |first4=S. Hong |last5=Ripke |first5=Stephan |last6=Neale |first6=Benjamin M. |last7=Corvin |first7=Aiden |last8=Walters |first8=James T.R. |last9=Farh |first9=Kai-How |date=June 2018 |title=Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood |url=https://linkinghub.elsevier.com/retrieve/pii/S0002929718301101 |journal=The American Journal of Human Genetics |volume=102 |issue=6 |pages=1185–1194 |doi=10.1016/j.ajhg.2018.03.021 |issn=0002-9297 |pmc=PMC5993419 |pmid=29754766}}</ref> 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 statistic]]s of the [[single-nucleotide polymorphism]]s (SNPs) from the GWAS. Here, the "linkage disequilibrium score" for a SNP "is the sum of LD r<sup>2</sup> measured with all other SNPs".<ref>{{Cite journal |last=Neale |first=Benjamin M. |last2=Price |first2=Alkes L. |last3=Daly |first3=Mark J. |last4=Patterson |first4=Nick |last5=Consortium |first5=Schizophrenia Working Group of the Psychiatric Genomics |last6=Yang |first6=Jian |last7=Ripke |first7=Stephan |last8=Finucane |first8=Hilary K. |last9=Loh |first9=Po-Ru |date=March 2015 |title=LD Score regression distinguishes confounding from polygenicity in genome-wide association studies |url=https://www.nature.com/articles/ng.3211 |journal=Nature Genetics |language=en |volume=47 |issue=3 |pages=291–295 |doi=10.1038/ng.3211 |issn=1546-1718 |pmc=PMC4495769 |pmid=25642630}}</ref> LDSC can be used to produce SNP-based [[heritability]] estimates, to partition this heritability into separate categories, and to calculate [[genetic correlation]]s between separate [[phenotype]]s. Because the LDSC approach relies only on summary statistics from an entire GWAS, it can be used efficiently even with very large sample sizes.<ref>{{Cite journal |last=Neale |first=Benjamin M. |last2=Evans |first2=David M. |last3=Gaunt |first3=Tom R. |last4=Paternoster |first4=Lavinia |last5=Anttila |first5=Verneri |last6=Bulik-Sullivan |first6=Brendan K. |last7=Price |first7=Alkes L. |last8=Finucane |first8=Hilary K. |last9=Warrington |first9=Nicole M. |date=2017-01-15 |title=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 |url=https://academic.oup.com/bioinformatics/article/33/2/272/2525718 |journal=Bioinformatics |language=en |volume=33 |issue=2 |pages=272–279 |doi=10.1093/bioinformatics/btw613 |issn=1367-4803 |pmc=PMC5542030 |pmid=27663502}}</ref> 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.<ref>{{Cite journal |last=Neale |first=Benjamin M. |last2=Price |first2=Alkes L. |last3=Daly |first3=Mark J. |last4=Robinson |first4=Elise B. |last5=Patterson |first5=Nick |last6=Perry |first6=John R. B. |last7=Duncan |first7=Laramie |last8=Consortium 3 |first8=Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control |last9=Consortium |first9=Psychiatric Genomics |date=November 2015 |title=An atlas of genetic correlations across human diseases and traits |url=https://www.nature.com/articles/ng.3406 |journal=Nature Genetics |language=en |volume=47 |issue=11 |pages=1236–1241 |doi=10.1038/ng.3406 |issn=1546-1718 |pmc=PMC4797329 |pmid=26414676}}</ref> There is also another extension of LDSC, known as '''stratified LD score regression''' (abbreviated '''SLDSR'''),<ref>{{Cite journal |last=Nivard |first=Michel G. |last2=Boomsma |first2=Dorret I. |last3=Consortium |first3=UK Brain Expression |last4=Bartels |first4=Meike |last5=Abdellaoui |first5=Abdel |last6=Jansen |first6=Rick |last7=Ip |first7=Hill F. |date=2018-09-01 |title=Characterizing the Relation Between Expression QTLs and Complex Traits: Exploring the Role of Tissue Specificity |url=https://link.springer.com/article/10.1007/s10519-018-9914-2 |journal=Behavior Genetics |language=en |volume=48 |issue=5 |pages=374–385 |doi=10.1007/s10519-018-9914-2 |issn=1573-3297 |pmc=PMC6097736 |pmid=30030655}}</ref> that takes into account [[genetic linkage]] between markers.<ref>{{Cite journal |last=Price |first=Alkes L. |last2=Neale |first2=Benjamin M. |last3=Patterson |first3=Nick |last4=Daly |first4=Mark J. |last5=Raychaudhuri |first5=Soumya |last6=Okada |first6=Yukinori |last7=Perry |first7=John R. B. |last8=Lindstrom |first8=Sara |last9=Stahl |first9=Eli |date=November 2015 |title=Partitioning heritability by functional annotation using genome-wide association summary statistics |url=https://www.nature.com/articles/ng.3404 |journal=Nature Genetics |language=en |volume=47 |issue=11 |pages=1228–1235 |doi=10.1038/ng.3404 |issn=1546-1718 |pmc=PMC4626285 |pmid=26414678}}</ref>
==References==
==References==
{{Reflist}}
{{Reflist}}

Revision as of 18:24, 17 December 2018

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 (abbreviated SLDSR),[5] that takes into account genetic linkage between markers.[6]

References

  1. ^ 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)
  2. ^ 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)
  3. ^ 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)
  4. ^ 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)
  5. ^ Nivard, Michel G.; Boomsma, Dorret I.; Consortium, UK Brain Expression; Bartels, Meike; Abdellaoui, Abdel; Jansen, Rick; Ip, Hill F. (2018-09-01). "Characterizing the Relation Between Expression QTLs and Complex Traits: Exploring the Role of Tissue Specificity". Behavior Genetics. 48 (5): 374–385. doi:10.1007/s10519-018-9914-2. ISSN 1573-3297. PMC 6097736. PMID 30030655.{{cite journal}}: CS1 maint: PMC format (link)
  6. ^ Price, Alkes L.; Neale, Benjamin M.; Patterson, Nick; Daly, Mark J.; Raychaudhuri, Soumya; Okada, Yukinori; Perry, John R. B.; Lindstrom, Sara; Stahl, Eli (November 2015). "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}}: CS1 maint: PMC format (link)
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