Abstract
BackgroundThere is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance.ResultsA total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization.ConclusionsThe CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.
Highlights
There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting
We present here a survey of the various methods used in the Challenge and summarize the opinions and attitudes of the contestants after the fact regarding the practice of clinical-grade genome-scale diagnostics for clinical practice
Three families were identified by the Manton Center for Orphan Disease Research to serve as test cases for the CLARITY challenge on the basis of having a child with clinical manifestations and/or pedigree structure suggestive of a likely genetic disease (Table 1)
Summary
There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. There have been a growing number of publicized successes in the application of genomic sequencing and interpretations for children with rare diseases of unknown etiology and patients with refractory cancers [4,5,6,7,8,9,10,11] This has led to a growing expectation that clinical whole exome sequencing (WES) or whole genome sequencing (WGS) services will soon be standard practice for a much larger population of patients. There is a large methodological armamentarium for assembling genomic reads into a sequence, detecting variation, interpreting the clinical significance of specific sequence variants, and compiling a clinically usable report. Just how these methods are used in context, and in what combination, all critically impact the quality of genomically informed diagnoses. Many studies have utilized WES datasets essentially as large gene panels, interrogating data for only a small set of candidate genes determined based on clinical presentations [13], while others have utilized the entire datasets to identify and qualify mutations anywhere in the genome [9]
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