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Clinically Responsive Genomic Analysis Pipelines: Elements to Improve Detection Rate and Efficiency.

Samantha Leigh Sundercombe1, Marina Berbic2, Carey-Anne Evans3

  • 1NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia.

The Journal of Molecular Diagnostics : JMD
|May 7, 2021
PubMed
Summary
This summary is machine-generated.

Customizing the Genomic Annotation and Interpretation Application (GAIA) bioinformatics pipeline improved diagnostic rates for mendelian disorders. These genomic analysis pipeline enhancements increased efficiency and cost-effectiveness in clinical settings.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Clinical Diagnostics

Background:

  • Massively parallel sequencing significantly enhances diagnostic rates for mendelian disorders.
  • Bioinformatic pipelines are crucial for analyzing genomic data and identifying disease-causing variants.
  • Clinical needs necessitate continuous improvement of diagnostic genomic pipelines.

Purpose of the Study:

  • To assess the impact of custom alterations to a diagnostic genomic bioinformatic pipeline on diagnostic rates and efficiency.
  • To derive practice recommendations for genomic analysis pipelines based on clinical utility.
  • To evaluate the cost-effectiveness of pipeline improvements.

Main Methods:

  • The Genomic Annotation and Interpretation Application (GAIA) pipeline was modified to improve variant detection and prioritization for mendelian disorders.
  • Reanalysis of previously negative cases was conducted using the enhanced GAIA pipeline.
  • Improvements included integrating PubMed searches for gene-disease associations, a process for calling low-quality variants (QPatch), and gene symbol nomenclature consistency checking.

Main Results:

  • The enhanced GAIA pipeline demonstrated increased diagnostic sensitivity for mendelian disorders.
  • Pipeline modifications led to a reduction in staff costs, with savings of US$844.34 per additional diagnosis.
  • The study identified specific improvements that enhance the pipeline's effectiveness.

Conclusions:

  • Clinically responsive improvements to bioinformatics pipelines enhance diagnostic sensitivity.
  • Optimized genomic analysis pipelines increase cost-effectiveness in clinical practice.
  • The study provides recommendations for essential genomic analysis pipeline requirements.