Strategies for exome and genome sequence data analysis in disease-gene discovery projects

Authors

  • PN Robinson,

    Corresponding author
    1. Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
    2. Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Berlin, Germany
    3. Max-Planck-Institut für Molekulare Genetik, Berlin, Germany
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  • P Krawitz,

    1. Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
    2. Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Berlin, Germany
    3. Max-Planck-Institut für Molekulare Genetik, Berlin, Germany
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  • S Mundlos

    1. Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
    2. Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Berlin, Germany
    3. Max-Planck-Institut für Molekulare Genetik, Berlin, Germany
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PD Dr. med. Peter N. Robinson, Institut für Medizinische Genetik und Humangenetik, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin,Germany.
Tel.: +49 30 450569122;
fax: +49 30 450569915;
e-mail: peter.robinson@charite.de

Abstract

Robinson PN, Krawitz P, Mundlos S. Strategies for exome and genome sequence data analysis in disease-gene discovery projects.

In whole-exome sequencing (WES), target capture methods are used to enrich the sequences of the coding regions of genes from fragmented total genomic DNA, followed by massively parallel, ‘next-generation’ sequencing of the captured fragments. Since its introduction in 2009, WES has been successfully used in several disease-gene discovery projects, but the analysis of whole-exome sequence data can be challenging. In this overview, we present a summary of the main computational strategies that have been applied to identify novel disease genes in whole-exome data, including intersect filters, the search for de novo mutations, and the application of linkage mapping or inference of identity-by-descent (IBD) in family studies.

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