Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey.
Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey.
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更好地支持基因组变异数据集中合并的实验室工作流程建议：来自 CanVIG-UK 国家分子实验室调查的结果。
DOI：
10.1136/jmg-2023-109645
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发表时间：
2023
影响因子：
4
通讯作者：
Allen S
中科院分区：
文献类型：
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作者：
Allen S
背景国家和国际基因组数据的融合为研究和审计提供了机会，包括分析使不确定意义的变体的分类得到改进。对来自国家卫生服务（NHS）癌症易感基因检测的个人水平数据的审查2002-2023年提交给国家疾病登记服务中心的研究报告显示，参与实验室在以下方面存在异质性：（1）提交数据的结构、质量和完整性，以及（2）数据在当地收集提交的难易程度。我们对51名临床科学家进行了一项封闭的在线调查，这些科学家提供了代表英格兰和威尔士17个NHS分子遗传实验室中所有17个的一致回答，这些实验室承担NHS癌症易感基因诊断分析。该调查包括18个问题有关的“下一代测序工作流程”（11），“变异分类”（3）和“表型上下文”（4）。结果广泛不同的过程中，变异数据转移到他们的本地LIMS（实验室信息管理系统），格式的变异存储在LIMS和保留在本地LIMS的变异类别。不同的地方规定和工作流程的变异分类也报道，包括提供的资源和分类stored.ConclusionThe调查的反应说明异构实验室工作流程的基因组变异数据从本地LIMS集中提交的准备。工作流程通常是劳动密集型和低效的，涉及多个手动步骤，这会引入错误的机会。这些调查结果和采纳相应的建议可能有助于改善实验室检查结果，更好地促进提交数据进行集中合并。
BackgroundNational and international amalgamation of genomic data offers opportunity for research and audit, including analyses enabling improved classification of variants of uncertain significance. Review of individual-level data from National Health Service (NHS) testing of cancer susceptibility genes (2002–2023) submitted to the National Disease Registration Service revealed heterogeneity across participating laboratories regarding (1) the structure, quality and completeness of submitted data, and (2) the ease with which that data could be assembled locally for submission.MethodsIn May 2023, we undertook a closed online survey of 51 clinical scientists who provided consensus responses representing all 17 of 17 NHS molecular genetic laboratories in England and Wales which undertake NHS diagnostic analyses of cancer susceptibility genes. The survey included 18 questions relating to ‘next-generation sequencing workflow’ (11), ‘variant classification’ (3) and ‘phenotypical context’ (4).ResultsWidely differing processes were reported for transfer of variant data into their local LIMS (Laboratory Information Management System), for the formatting in which the variants are stored in the LIMS and which classes of variants are retained in the local LIMS. Differing local provisions and workflow for variant classifications were also reported, including the resources provided and the mechanisms by which classifications are stored.ConclusionThe survey responses illustrate heterogeneous laboratory workflow for preparation of genomic variant data from local LIMS for centralised submission. Workflow is often labour-intensive and inefficient, involving multiple manual steps which introduce opportunities for error. These survey findings and adoption of the concomitant recommendations may support improvement in laboratory dataflows, better facilitating submission of data for central amalgamation.