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MSeqDR 快速线粒体分析(QM):结合表型指导的变异解释和机器学习分类器辅助原发性线粒体疾病的遗传诊断。

MSeqDR Quick-Mitome (QM): Combining Phenotype-Guided Variant Interpretation and Machine Learning Classifiers to Aid Primary Mitochondrial Disease Genetic Diagnosis.

机构信息

Center for Personalized Medicine, Department of Pathology & Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, California, USA.

Mitochondrial Medicine Frontier Program, Division of Human Genetics, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.

出版信息

Curr Protoc. 2024 Jan;4(1):e955. doi: 10.1002/cpz1.955.

Abstract

The international Mitochondrial Disease Sequence Data Resource Consortium (MSeqDR) Quick-Mitome (QM) is a web-based platform enabling automated variant interpretation of whole-exome sequencing (WES) datasets for the genetic diagnosis of primary mitochondrial diseases (PMD). Designed specifically to address the unique dual genome nature of PMD etiologies, QM includes features for both nuclear and mitochondrial DNA (mtDNA) genome analysis. QM requires VCF variant lists, HPO ID clinical phenotypes, and pedigree files for multiple-sample VCF inputs. QM maps phenotypes to HPO terms before analysis. QM analysis requires 2 to 20 min for 100,000 variants on an 8-vCPU AWS server using Exomiser's "PASS_ONLY" mode for nuclear variants. QM ranks variants based on allele frequency, phenotype-gene association, functional impact, and inheritance mode. Variants are further annotated with multiple data sources such as OMIM, ClinVar, dbNSFP, gnoMAD, MITOMAP, and MSeqDR. In addition to standard Exomiser results, QM generates an Analysis Report and QM Integrated Report with add-on mtDNA-specific analyses, including haplogroup prediction with Phy-Mer, heteroplasmy calculation, and mvTool annotations. We developed the Mitochondrial Disease Variant (MDV) classifier using XGBoost to predict variant pathogenicity for PMD. The MDV classifier was trained on >120 features and performance benchmarking showed that it correctly classified >98% of nuclear gene variants as being pathogenic or benign, and predicted PMD-causing variants with 94% precision. The MSeqDR QM server is an open-access resource for phenotype-driven dual-genome analyses for PMD diagnosis by the global mitochondrial disease community. It is publicly available for non-commercial, non-clinical research use at https://mseqdr.org/quickmitome.php. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Standardizing clinical phenotypes into human phenotype ontology (HPO) terms as the phenotype input for Quick-Mitome (QM) Basic Protocol 2: Prepare the pedigree input for multiple-sample VCF Basic Protocol 3: Quick-Mitome (QM) analysis Basic Protocol 4: Reviewing and understanding the QM Integrated Report and Analysis Report.

摘要

国际线粒体疾病序列数据资源联盟(MSeqDR)快速粒体(QM)是一个基于网络的平台,能够自动解释全外显子组测序(WES)数据集的变体,用于原发性线粒体疾病(PMD)的遗传诊断。QM 专为解决 PMD 病因的独特双重基因组性质而设计,包括核和线粒体 DNA(mtDNA)基因组分析的功能。QM 需要 VCF 变体列表、HPO ID 临床表型和多个样本 VCF 输入的家系文件。QM 在分析之前将表型映射到 HPO 术语。QM 分析使用 Exomiser 的“PASS_ONLY”模式在 8 个 CPU 的 AWS 服务器上对 100,000 个变体进行分析,需要 2 到 20 分钟。QM 根据等位基因频率、表型-基因关联、功能影响和遗传模式对变体进行排名。变体进一步使用多种数据源进行注释,例如 OMIM、ClinVar、dbNSFP、gnoMAD、MITOMAP 和 MSeqDR。除了标准的 Exomiser 结果外,QM 还生成分析报告和 QM 综合报告,并提供附加的 mtDNA 特定分析,包括 Phy-Mer 的单倍群预测、异质性计算和 mvTool 注释。我们使用 XGBoost 开发了线粒体疾病变体(MDV)分类器,用于预测 PMD 的变体致病性。MDV 分类器基于 >120 个特征进行训练,性能基准测试表明,它正确地将 >98%的核基因变体分类为致病性或良性,并以 94%的精度预测导致 PMD 的变体。MSeqDR QM 服务器是一个开放访问的资源,用于全球线粒体疾病社区进行 PMD 诊断的表型驱动的双重基因组分析。它可在非商业、非临床研究中在 https://mseqdr.org/quickmitome.php 上免费使用。©2024 威利期刊 LLC。基本方案 1:将临床表型标准化为人类表型本体(HPO)术语,作为 Quick-Mitome(QM)的表型输入基本方案 2:准备多个样本 VCF 的家系输入基本方案 3:Quick-Mitome(QM)分析基本方案 4:查看和理解 QM 综合报告和分析报告。

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