PT  - JOURNAL ARTICLE
AU  - Elliot S. Gershon
AU  - Godfrey Pearlson
AU  - Matcheri S. Keshavan
AU  - Carol Tamminga
AU  - Brett Clementz
AU  - Peter F. Buckley
AU  - Ney Alliey-Rodriguez
AU  - Chunyu Liu
AU  - John A. Sweeney
AU  - Sarah Keedy
AU  - Shashwath Meda
AU  - Neeraj Tandon
AU  - Rebecca Shafee
AU  - Jeffrey R. Bishop
AU  - Elena I. Ivleva
TI  - Genetic Analysis of Deep Phenotyping Projects in Common Disorders
AID  - 10.1101/197459
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 197459
4099  - http://biorxiv.org/content/early/2017/10/02/197459.short
4100  - http://biorxiv.org/content/early/2017/10/02/197459.full
AB  - Several studies of complex psychotic disorders with large numbers of neurobiological phenotypes are currently under way, in living patients and controls, and on assemblies of brain specimens. Genetic analyses of such data typically present challenges, because of the choice of underlying hypotheses on genetic architecture of the studied disorders and phenotypes, large numbers of phenotypes, the appropriate multiple testing corrections, limited numbers of subjects, imputations required on missing phenotypes and genotypes, and the cross-disciplinary nature of the phenotype measures. Advances in genotype and phenotype imputation, and in genome-wide association (GWAS) methods, are useful in dealing with these challenges. As compared with the more traditional single-trait analyses, deep phenotyping with simultaneous genome-wide analyses serves as a discovery tool for previously unsuspected relationships of phenotypic traits with each other, and with specific molecular involvements.