Genome-wide linkage scan, fine mapping, and haplotype analysis in a large, inbred, Arab Israeli pedigree suggest a schizophrenia susceptibility locus on chromosome 20p13

2008 ◽  
Vol 147B (2) ◽  
pp. 209-215 ◽  
Author(s):  
Omri Teltsh ◽  
Kyra Kanyas ◽  
Osnat Karni ◽  
Adi Levi ◽  
Mira Korner ◽  
...  
2005 ◽  
Vol 13 (6) ◽  
pp. 763-771 ◽  
Author(s):  
Adi Levi ◽  
Yoav Kohn ◽  
Kyra Kanyas ◽  
Daniela Amann ◽  
Chi-Un Pae ◽  
...  

2002 ◽  
Vol 54 (4) ◽  
pp. 199-209 ◽  
Author(s):  
Linda M. Brzustowicz ◽  
Jared E. Hayter ◽  
Kathleen A. Hodgkinson ◽  
Eva W.C. Chow ◽  
Anne S. Bassett

2018 ◽  
Vol 79 (3) ◽  
pp. 467-481 ◽  
Author(s):  
Melissa A. Buckley ◽  
Nicholas T. Woods ◽  
Jonathan P. Tyrer ◽  
Gustavo Mendoza-Fandiño ◽  
Kate Lawrenson ◽  
...  

Author(s):  
Jianhua Wang ◽  
Dandan Huang ◽  
Yao Zhou ◽  
Hongcheng Yao ◽  
Huanhuan Liu ◽  
...  

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.


Author(s):  
C. Robert Cloninger ◽  
Charles A. Kaufmann ◽  
Stephen V. Faraone ◽  
Dolores Malaspina ◽  
Dragan M. Svrakic ◽  
...  

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