nanotatoR: a tool for enhanced annotation of genomic structural variants.
nanotatoR: a tool for enhanced annotation of genomic structural variants.
复制标题
DOI：
10.1186/s12864-020-07182-w
复制
发表时间：
2021-01-06
期刊：
影响因子：
4.4
通讯作者：
Vilain E
中科院分区：
文献类型：
--
作者：
Bhattacharya S;Barseghyan H;Délot EC;Vilain E
全基因组测序在鉴定小变异方面是有效的，但由于它是基于短读数，对结构变异（SVs）的评估是有限的。光学基因组定位（OGM）的出现，利用长荧光标记的DNA分子进行从头基因组组装和SV呼叫，增加了SV检测的灵敏度和特异性。然而，与小变异注释工具相比，基于ogm的SV注释软件发展较少，现有的SV注释工具不能为变异致病性的确定提供足够的信息。我们开发了一个基于r的包，nanotatoR，它提供了全面的注释作为SV分类工具。nanotatoR使用外部（DGV； DECIPHER; Bionano Genomics BNDB）和内部（用户定义的）数据库来估计SV频率。基于grch37 /38的人类基因组参考BED文件用于标注具有重叠、上游和下游基因的sv。计算最近基因的重叠百分比和距离，并可用于过滤。根据患者的表型从公共数据库中提取一个主要基因列表，用于过滤重叠的sv基因，为分析人员提供一种简单的方法来确定变异的优先级。如果可用，可以提取重叠或附近感兴趣的基因的表达（例如，从RNA-Seq数据集中，允许用户评估SVs对转录组的影响）。大多数质量控制过滤参数可由用户定制。输出以Excel文件格式给出，根据SV类型和继承模式（INDELs，倒置，易位，de novo等）细分为多个表。nanotatoR通过了Bioconductor的所有质量和运行时间标准，并于2019年4月发布。我们使用公开可用的参考数据集来评估nanotatoR的注释能力：单样本NA12878，用两种类型的酶标记映射，以及NA24143三种。nanotatoR还能够准确地过滤杜氏肌营养不良患者队列中已知的致病变异，我们之前已经证明了OGM的诊断能力。广泛的注释使用户能够快速识别潜在的致病性SVs，这是在临床环境中使用OGM的关键一步。
Whole genome sequencing is effective at identification of small variants, but because it is based on short reads, assessment of structural variants (SVs) is limited. The advent of Optical Genome Mapping (OGM), which utilizes long fluorescently labeled DNA molecules for de novo genome assembly and SV calling, has allowed for increased sensitivity and specificity in SV detection. However, compared to small variant annotation tools, OGM-based SV annotation software has seen little development, and currently available SV annotation tools do not provide sufficient information for determination of variant pathogenicity. We developed an R-based package, nanotatoR, which provides comprehensive annotation as a tool for SV classification. nanotatoR uses both external (DGV; DECIPHER; Bionano Genomics BNDB) and internal (user-defined) databases to estimate SV frequency. Human genome reference GRCh37/38-based BED files are used to annotate SVs with overlapping, upstream, and downstream genes. Overlap percentages and distances for nearest genes are calculated and can be used for filtration. A primary gene list is extracted from public databases based on the patient’s phenotype and used to filter genes overlapping SVs, providing the analyst with an easy way to prioritize variants. If available, expression of overlapping or nearby genes of interest is extracted (e.g. from an RNA-Seq dataset, allowing the user to assess the effects of SVs on the transcriptome). Most quality-control filtration parameters are customizable by the user. The output is given in an Excel file format, subdivided into multiple sheets based on SV type and inheritance pattern (INDELs, inversions, translocations, de novo, etc.). nanotatoR passed all quality and run time criteria of Bioconductor, where it was accepted in the April 2019 release. We evaluated nanotatoR’s annotation capabilities using publicly available reference datasets: the singleton sample NA12878, mapped with two types of enzyme labeling, and the NA24143 trio. nanotatoR was also able to accurately filter the known pathogenic variants in a cohort of patients with Duchenne Muscular Dystrophy for which we had previously demonstrated the diagnostic ability of OGM. The extensive annotation enables users to rapidly identify potential pathogenic SVs, a critical step toward use of OGM in the clinical setting.
登录
查看更多内容
影响因子：
--
作者：
Jaratlerdsiri W;Chan EKF;Petersen DC;Yang C;Croucher PI;Bornman MSR;Sheth P;Hayes VM
通讯作者：
Hayes VM
影响因子：
12.3
作者：
Barseghyan H;Tang W;Wang RT;Almalvez M;Segura E;Bramble MS;Lipson A;Douine ED;Lee H;Délot EC;Nelson SF;Vilain E
通讯作者：
Vilain E
影响因子：
46.9
作者：
Jain M;Koren S;Miga KH;Quick J;Rand AC;Sasani TA;Tyson JR;Beggs AD;Dilthey AT;Fiddes IT;Malla S;Marriott H;Nieto T;O'Grady J;Olsen HE;Pedersen BS;Rhie A;Richardson H;Quinlan AR;Snutch TP;Tee L;Paten B;Phillippy AM;Simpson JT;Loman NJ;Loose M
通讯作者：
Loose M
影响因子：
5.8
作者：
Geoffroy, Veronique;Herenger, Yvan;Muller, Jean
通讯作者：
Muller, Jean
影响因子：
3.8
作者：
Du, Chen;Mark, Dorothea;Steinemann, Doris
通讯作者：
Steinemann, Doris