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CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations.

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  • معلومة اضافية
    • المصدر:
      Publisher: BioMed Central Country of Publication: England NLM ID: 101475844 Publication Model: Electronic Cited Medium: Internet ISSN: 1756-994X (Electronic) Linking ISSN: 1756994X NLM ISO Abbreviation: Genome Med Subsets: MEDLINE
    • بيانات النشر:
      Original Publication: [London] : BioMed Central
    • الموضوع:
      Exome* ; Genetic Variation* ; Software*; Computational Biology/*methods; Gene Frequency ; Genetic Association Studies/methods ; Humans ; INDEL Mutation ; Machine Learning ; Molecular Diagnostic Techniques ; Molecular Sequence Annotation ; Polymorphism, Single Nucleotide ; ROC Curve ; Reproducibility of Results
    • نبذة مختصرة :
      Exome sequencing is now mainstream in clinical practice. However, identification of pathogenic Mendelian variants remains time-consuming, in part, because the limited accuracy of current computational prediction methods requires manual classification by experts. Here we introduce CAPICE, a new machine-learning-based method for prioritizing pathogenic variants, including SNVs and short InDels. CAPICE outperforms the best general (CADD, GAVIN) and consequence-type-specific (REVEL, ClinPred) computational prediction methods, for both rare and ultra-rare variants. CAPICE is easily added to diagnostic pipelines as pre-computed score file or command-line software, or using online MOLGENIS web service with API. Download CAPICE for free and open-source (LGPLv3) at https://github.com/molgenis/capice .
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    • Contributed Indexing:
      Keywords: Allele frequency; Clinical genetics; Exome sequencing; Genome diagnostics; Machine learning; Molecular consequence; Variant pathogenicity prediction
    • الموضوع:
      Date Created: 20200825 Date Completed: 20210803 Latest Revision: 20231112
    • الموضوع:
      20250114
    • الرقم المعرف:
      PMC7446154
    • الرقم المعرف:
      10.1186/s13073-020-00775-w
    • الرقم المعرف:
      32831124