Integrating Massively Parallel Sequencing into Diagnostic Workflows and Managing the Annotation and Clinical Interpretation Challenge

Authors

  • Karin S. Kassahn,

    Corresponding author
    1. Genetic and Molecular Pathology, SA Pathology, Women's and Children's Hospital, North Adelaide, South Australia, Australia
    2. School of Molecular and Biomedical Science, University of Adelaide, Adelaide, South Australia, Australia
    • Correspondence to: Karin S. Kassahn, SA Pathology, Genetic and Molecular Pathology, Women's and Children's Hospital Level 9, Rieger Building, North Adelaide, South Australia 5006, Australia. E-mail: karin.kassahn@health.sa.gov.au

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  • Hamish S. Scott,

    1. Molecular Pathology and Centre for Cancer Biology, SA Pathology, Adelaide, South Australia, Australia
    2. School of Molecular and Biomedical Science, University of Adelaide, Adelaide, South Australia, Australia
    3. School of Medicine, University of Adelaide, Adelaide, South Australia, Australia
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  • Melody C. Caramins

    1. School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
    2. SDS Pathology, Waterloo Road, Sydney, New South Wales, Australia
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  • Communicated by Arupa Ganguly

ABSTRACT

Massively parallel sequencing has become a powerful tool for the clinical management of patients with applications in diagnosis, guidance of treatment, prediction of drug response, and carrier screening. A considerable challenge for the clinical implementation of these technologies is the management of the vast amount of sequence data generated, in particular the annotation and clinical interpretation of genomic variants. Here, we describe annotation steps that can be automated and common strategies employed for variant prioritization. The definition of best practice standards for variant annotation and prioritization is still ongoing; at present, there is limited consensus regarding an optimal clinical sequencing pipeline. We provide considerations to help define these. For the first time, clinical genetics and genomics is not limited by our ability to sequence, but our ability to clinically interpret and use genomic information in health management. We argue that the development of standardized variant annotation and interpretation approaches and software tools implementing these warrants further support. As we gain a better understanding of the significance of genomic variation through research, patients will be able to benefit from the full scope that these technologies offer.

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