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Peristera Paschou

Researcher at Purdue University

Publications -  107
Citations -  5590

Peristera Paschou is an academic researcher from Purdue University. The author has contributed to research in topics: Tourette syndrome & Population. The author has an hindex of 30, co-authored 92 publications receiving 4046 citations. Previous affiliations of Peristera Paschou include Semel Institute for Neuroscience and Human Behavior & Yale University.

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Analysis of shared heritability in common disorders of the brain

Verneri Anttila, +720 more
- 22 Jun 2018 - 
TL;DR: It is demonstrated that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine, and it is shown that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures.
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Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Phil Lee, +606 more
- 12 Dec 2019 - 
TL;DR: Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes.
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ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

Paul M. Thompson, +213 more
TL;DR: This review summarizes the last decade of work by the ENIGMA Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease, and highlights the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings.
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PCA-correlated SNPs for structure identification in worldwide human populations.

TL;DR: A novel algorithm is presented that is effectively used for the analysis of admixed populations without having to trace the origin of individuals, and can be easily applied on large genome-wide datasets, facilitating the identification of population substructure, stratification assessment in multi-stage whole-genome association studies, and the study of demographic history in human populations.