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               <mods:identifier type="citation">Genet Med. 2023 Apr;25(4):100018.</mods:identifier>
               <mods:identifier type="uri">http://hdl.handle.net/20.500.12105/15629</mods:identifier>
               <mods:identifier type="pubmedID">36681873</mods:identifier>
               <mods:identifier type="doi">10.1016/j.gim.2023.100018</mods:identifier>
               <mods:identifier type="e-issn">1530-0366</mods:identifier>
               <mods:identifier type="journal">Genetics in medicine : official journal of the American College of Medical Genetics</mods:identifier>
               <mods:abstract>Purpose: Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the "ClinVar low-hanging fruit" reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods: Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results: We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion: The "ClinVar low-hanging fruit" analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock.</mods:abstract>
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                  <mods:title>A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing</mods:title>
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