计算机科学
序列(生物学)
人工智能
数据挖掘
鉴定(生物学)
特征(语言学)
情报检索
模式识别(心理学)
钥匙(锁)
自然语言处理
作者
Leslie Biesecker,Heidi Rehm,Ahmad Abou Tayoun,Jonathan Berg,David Bick,Alicia Byrne,Elizabeth Chao,Julie Gastier-Foster,Izabela Karbassi,Ann Moyer,Anne O'Donnell-Luria,Sharon Plon,Neethu Shah,Lisa M. Vincent,Nicola Whiffen
出处
期刊:
[Elsevier BV]
日期:2026-01-01
卷期号:4: 104084-104084
被引量:1
标识
DOI:10.1016/j.gimo.2026.104084
摘要
The American College of Medical Genetics and Genomics (ACMG), Association for Molecular Pathology (AMP), College of American Pathologists (CAP) and Clinical Genome Resource (ClinGen), are working on updated standards for sequence variant classification (SVC), referred to as SVC v4.0. SVC v4.0 uses a Bayesian, points-based system and flow diagrams that guide curators through evidence application. To evaluate the validity and usability of the draft standards, we launched a pilot involving clinical laboratories with expertise in variant classification.
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