Author

Steven A McCarroll

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetics· 2 Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 4 Approach:statistical model· 4 Research Focus:GWAS / association mapping· 3 Assay:GWAS summary statistics· 3 Research Focus:polygenic risk· 2 Approach:deep learning· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Stephan RipkeiD· 3 shared Alexander GuseviD· 2 shared Benjamin M Neale· 2 shared Bogdan Pasaniuc· 2 shared Eli StahliD· 2 shared Giulio GenoveseiD· 2 shared Mark Daly· 2 shared Naomi R Wray· 2 shared

Activity by Year

2014-2016 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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3 shared papersGenomics

Stephan RipkeORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Common schizophrenia alleles are enriched in mutation-intolerant genes and maintained by background selection

Antonio F Pardiñas, Peter Holmans, Andrew J Pocklington, Valentina Escott-Price, Stephan Ripke, Noa Carrera, Sophie E Legge, Sophie Bishop, Darren Cameron, Marian L Hamshere, Jun Han, Leon Hubbard, Amy Lynham, Kiran Mantripragada, Elliott Rees, , James T R Walters

This study identifies 50 novel schizophrenia GWAS loci and shows common risk variants are enriched in mutation-intolerant genes maintained by background selection.

bioRxiv · Aug 9, 2016Genomics

Ultra-rare disruptive and damaging mutations influence educational attainment in the general population

Andrea Ganna, Giulio Genovese, Daniel P Howrigan, Andrea Byrnes, Mitja Kurki, Seyedeh M Zekavat, Christopher W Whelan, Robert E Handsaker, Mart Kals, Alex Bloemendal, Jonathan M Bloom, Jacqueline I Goldstein, Timothy Poterba, Cotton Seed, Michel G Nivard, , Benjamin M Neale

This study finds that ultra-rare disruptive variants in highly constrained genes are associated with reduced educational attainment in the general population.

bioRxiv · Jun 7, 2016Genetics

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Bjarni Vilhjalmsson, Jian Yang, Hilary Kiyo Finucane, Alexander Gusev, Sara Lindstrom, Stephan Ripke, Giulio Genovese, Po-Ru Loh, Gaurav Bhatia, Ron Do, Tristian Hayeck, Hong-Hee Won, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) study the Discovery, Sekar Kathiresan, , Nick J Patte

This paper introduces LDpred, a method that improves polygenic risk score accuracy by modeling linkage disequilibrium, showing increased R2 values in schizophrenia and multiple sclerosis datasets.

The American Journal of Human Genetics · Oct 1, 2015Peer-reviewedBioinformatics

Regulatory variants explain much more heritability than coding variants across 11 common diseases

Alexander Gusev, S Hong Lee, Benjamin M Neale, Gosia Trynka, Bjarni J Vilhjalmsson, Hilary Finucane, Han Xu, Chongzhi Zang, Stephan Ripke, Eli Stahl, n/a Schizophrenia Working Group of the PGC, n/a SWE-SCZ Consortium, Anna K Kahler, Christina M Hultman, Shaun M Purcell, , Alkes L Price

The paper shows regulatory variants explain significantly more heritability than coding variants for 11 diseases, using imputed data across 218 cell types.

bioRxiv · Apr 21, 2014 · PreprintGenetics