Author
Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.
9 papers
Recent·Most cited
Sang Hong Lee, W.M. Shalanee P. Weerasinghe, Naomi Wray, Michael Goddard, Julius Van der Werf
This paper demonstrates that genomic prediction accuracy can be significantly improved by using smaller effective population sizes and closer relationships in discovery sets, supporting stratified medicine approaches.
Scientific Reports · Feb 9, 2017Peer-reviewedGenetics
Jian Yang, Sang Hong Lee, Naomi R. Wray, Michael E. Goddard, Peter M Visscher
The paper refutes claims that GCTA cannot reliably estimate heritability, showing the results are consistent with GCTA theory.
Proceedings of the National Academy of Sciences · Jul 25, 2016Peer-reviewedGenetics
Gaurav Bhatia, Alexander Gusev, Po-Ru Loh, Hilary Finucane, Bjarni J. Vilhjálmsson, Stephan Ripke, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Shaun Purcell, Eli Stahl, Mark Daly, Teresa R de Candia, Sang Hong Lee, Benjamin M Neale, Matthew C. Keller, Noah A. Zaitlen, , Alkes L. Price
This study shows that subtle population stratification can confound heritability estimates from rare variants, even after standard corrections, suggesting the need for better stratification control in genetic studies.
bioRxiv · Apr 13, 2016 · PreprintGenetics
Guo-Bo Chen, Sang Hong Lee, Matthew R Robinson, Maciej Trzaskowski, Zhi-Xiang Zhu, Thomas W Winkler, Felix R Day, Damien C Croteau-Chonka, Andrew R Wood, Adam E Locke, Zoltán Kutalik, Ruth J F Loos, Timothy M Frayling, Joel N Hirschhorn, Jian Yang, , Peter M Visscher
This study introduces metrics and tools to assess quality control in genome-wide association meta-analyses using summary statistics from multiple cohorts.
bioRxiv · Dec 6, 2015 · PreprintGenetics
Sang Hong Lee, Julius van der Werf
The paper introduces MTG2, an efficient algorithm for multivariate linear mixed model analysis using genomic data, showing speeds up to 1000 times faster than standard REML software.
bioRxiv · Dec 2, 2015Genetics
Guo-Bo Chen, Sang Hong Lee, Zhi-Xiang Zhu, Beben Benyamin, Matthew R Robinson
EigenGWAS uses GWAS on eigenvectors to detect selection signals in structured populations, identifying loci under selection along ancestry gradients.
bioRxiv · Nov 17, 2015Genetics
The paper shows that simplified linkage equilibrium SNP simulations (SLES) led to inflated correlations between eigenvectors and disease status, affecting REML estimates, but real data analyses showed no such difference between REML and PCGC.
bioRxiv · Aug 27, 2015Genetics
Gaurav Bhatia, Alexander Gusev, Po-Ru Loh, Bjarni J. Vilhjálmsson, Stephan Ripke, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Shaun Purcell, Eli Stahl, Mark Daly, Teresa R de Candia, Kenneth S. Kendler, Michael C O’Donovan, Sang Hong Lee, Naomi R. Wray, Benjamin M Neale, , Alkes L. Price
The paper shows that haplotypes of common SNPs explain more heritability of complex diseases than individual SNPs alone.
bioRxiv · Jul 12, 2015 · PreprintGenetics
Po-Ru Loh, Gaurav Bhatia, Alexander Gusev, Hilary K Finucane, Brendan K Bulik-Sullivan, Samuela J Pollack, Schizophrenia Working Group of the Psychiatric Genomics Consortiumy, Teresa R de Candia, Sang Hong Lee, Naomi R Wray, Kenneth S Kendler, Michael C O’Donovan, Benjamin M Neale, Nick Patterson, Alkes L Price
The paper analyzes the genetic architecture of schizophrenia and nine complex diseases using a fast variance components analysis, finding polygenic patterns and significant genetic correlations.
bioRxiv · Jun 5, 2015 · PreprintGenetics