Author

Patrick F Sullivan

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· 3 Genomics· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 5 Organism:human· 4 Assay:bulk RNA-seq· 3 Research Focus:GWAS / association mapping· 3 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:GWAS summary statistics· 1 Organism:mouse· 1

Frequent Co-Authors

Alexander GuseviD· 3 shared Alkes L Price· 3 shared Bogdan Pasaniuc· 3 shared Shaun M Purcell· 3 shared Benjamin M Neale· 2 shared Steven A McCarroll· 2 shared A. Ercument Cicek· 1 shared Aarno Palotie· 1 shared

Activity by Year

2014-2018 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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3 shared papersGenetics

Alexander GusevORCID

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Author profile →

5 papers

Recent·Most cited

Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights

Alexander Gusev, Nick Mancuso, Hilary K Finucane, Yakir Reshef, Lingyun Song, Alexias Safi, Edwin Oh, SCZ Working Group of the Psychiatric Genomics Cons, Steven McCaroll, Benjamin Neale, Roel Ophoff, Michael C O'Donovan, Nicholas Katsanis, Gregory E Crawford, Patrick F Sullivan, , Alkes L Price

This study connects schizophrenia GWAS findings to specific genes, tissues, and regulatory mechanisms through transcriptome-wide and chromatin activity analyses.

Nature Genetics · Apr 9, 2018Peer-reviewedGenomics

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

Gene Expression Elucidates Functional Impact of Polygenic Risk for Schizophrenia

Menachem Fromer, Panos Roussos, Solveig K Sieberts, Jessica S Johnson, David H Kavanagh, Thanneer M Perumal, Douglas M Ruderfer, Edwin C Oh, Aaron Topol, Hardik R Shah, Lambertus L Klei, Robin Kramer, Dalila Pinto, Zeynep H Gumus, A. Ercument Cicek, , Lara M Mangravit

The paper uses gene expression data from schizophrenia cases and controls to show that common variants at 20% of schizophrenia risk loci regulate brain gene expression, with functional impacts on neural progenitor cells and zebrafish neuroanatomy.

bioRxiv · May 9, 2016Genomics

Integrative approaches for large-scale transcriptome-wide association studies

Alexander Gusev, Arthur Ko, Huwenbo Shi, Gaurav Bhatia, Wonil Chung, Brenda WJ Penninx, Rick Jansen, Eco JC de Geus, Dorret I Boomsma, Fred A Wright, Patrick F Sullivan, Elina Nikkola, Marcus Alvarez, Mete Civelek, Aldons J Lusis, , Bogdan Pasaniuc

The paper integrates gene expression and GWAS data to identify novel genes associated with obesity-related traits.

bioRxiv · Aug 10, 2015Genetics

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