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Uncovering obsessive-compulsive disorder risk genes in a pediatric cohort by high-resolution analysis of copy number variation.

Journal of neurodevelopmental disorders | 2016

Obsessive-compulsive disorder (OCD) is a heterogeneous neuropsychiatric condition, thought to have a significant genetic component. When onset occurs in childhood, affected individuals generally exhibit different characteristics from adult-onset OCD, including higher prevalence in males and increased heritability. Since neuropsychiatric conditions are associated with copy number variations (CNVs), we considered their potential role in the etiology of OCD.

Pubmed ID: 27777633 RIS Download

Research resources used in this publication

None found

Antibodies used in this publication

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Associated grants

  • Agency: NIMH NIH HHS, United States
    Id: R01 MH085300
  • Agency: NIMH NIH HHS, United States
    Id: R01 MH085321
  • Agency: NIMH NIH HHS, United States
    Id: R01 MH101493

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This is a list of tools and resources that we have found mentioned in this publication.


ExAc (tool)

RRID:SCR_004068

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. An aggregated data platform for genome sequencing data created by a coalition of investigators seeking to aggregate and harmonize exome sequencing data from a variety of large-scale sequencing projects, and to make summary data available for the wider scientific community. The data set provided on this website spans 61,486 unrelated individuals sequenced as part of various disease-specific and population genetic studies. They have removed individuals affected by severe pediatric disease, so this data set should serve as a useful reference set of allele frequencies for severe disease studies. All of the raw data from these projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects. They ask that you not publish global (genome-wide) analyses of these data until after the ExAC flagship paper has been published, estimated to be in early 2015. If you''re uncertain which category your analyses fall into, please email them. The aggregation and release of summary data from the exomes collected by the Exome Aggregation Consortium has been approved by the Partners IRB (protocol 2013P001477, Genomic approaches to gene discovery in rare neuromuscular diseases).

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PLINK (tool)

RRID:SCR_001757

Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.

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GATK (tool)

RRID:SCR_001876

A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)

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Gene Set Enrichment Analysis (tool)

RRID:SCR_003199

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

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DECIPHER (tool)

RRID:SCR_006552

Interactive database which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance. Used to enhance clinical diagnosis by retrieving information from bioinformatics resources relevant to the imbalance found in the patient. Contributing to the DECIPHER database is a Consortium, comprising an international community of academic departments of clinical genetics. Each center maintains control of its own patient data (which are password protected within the center''''s own DECIPHER project) until patient consent is given to allow anonymous genomic and phenotypic data to become freely viewable within Ensembl and other genome browsers. Once data are shared, consortium members are able to gain access to the patient report and contact each other to discuss patients of mutual interest, thus facilitating the delineation of new microdeletion and microduplication syndromes.

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