Comparative linkage meta-analysis reveals regionally-distinct, disparate genetic architectures: application to bipolar disorder and schizophrenia

New high-throughput, population-based methods and next-generation sequencing capabilities hold great promise in the quest for common and rare variant discovery and in the search for "missing heritability." However, the optimal analytic strategies for approaching such data are still activel...

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Bibliographic Details
Published in:PloS one 2011-04, Vol.6 (4), p.e19073-e19073
Main Authors: Tang, Brady, Thornton-Wells, Tricia, Askland, Kathleen D
Format: Article
Language:English
Subjects:
Algorithms
Alleles
Biology
Bipolar disorder
Bipolar Disorder - genetics
Data processing
Genes
Genetic Linkage
Genetic Predisposition to Disease
Genetic research
Genome, Human
Genome-Wide Association Study
Genomes
Genomics
Heritability
Humans
Linkage analysis
Mental disorders
Meta-analysis
Models, Genetic
Models, Statistical
Oligonucleotide Array Sequence Analysis
Optimization
Pathogenesis
Polymorphism, Single Nucleotide
Population
Population (statistical)
Psychiatry
Schizophrenia
Schizophrenia - genetics
Statistical methods
Studies
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Description
Summary:New high-throughput, population-based methods and next-generation sequencing capabilities hold great promise in the quest for common and rare variant discovery and in the search for "missing heritability." However, the optimal analytic strategies for approaching such data are still actively debated, representing the latest rate-limiting step in genetic progress. Since it is likely a majority of common variants of modest effect have been identified through the application of tagSNP-based microarray platforms (i.e., GWAS), alternative approaches robust to detection of low-frequency (1-5% MAF) and rare (
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0019073