Genomic variant benchmark: if you cannot measure it, you cannot improve it

被引:8
|
作者
Majidian, Sina [1 ,2 ]
Agustinho, Daniel Paiva [3 ]
Chin, Chen-Shan [4 ]
Sedlazeck, Fritz J. [3 ,5 ]
Mahmoud, Medhat [3 ,6 ]
机构
[1] Univ Lausanne, Dept Computat Biol, CH-1015 Lausanne, Switzerland
[2] SIB Swiss Inst Bioinformat, CH-1015 Lausanne, Switzerland
[3] Baylor Coll Med, Human Genome Sequencing Ctr, Houston, TX 77030 USA
[4] Sema4 OpCo Inc, Stamford, CT 06405 USA
[5] Rice Univ, Dept Comp Sci, 6100 Main St, Houston, TX 77005 USA
[6] Baylor Coll Med, Dept Mol & Human Genet, Houston, TX 77030 USA
基金
美国国家卫生研究院; 瑞士国家科学基金会;
关键词
Genetic variation; SNPs; Indels; Structural variant; Benchmark datasets; Medical genes; Sequencing technology; SEQUENCE; ACCURACY; RESOURCE; ASSEMBLIES; MUTATIONS; DISCOVERY; GERMLINE; GENOTYPE; GRAPHS; GENES;
D O I
10.1186/s13059-023-03061-1
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Genomic benchmark datasets are essential to driving the field of genomics and bioinformatics. They provide a snapshot of the performances of sequencing technologies and analytical methods and highlight future challenges. However, they depend on sequencing technology, reference genome, and available benchmarking methods. Thus, creating a genomic benchmark dataset is laborious and highly challenging, often involving multiple sequencing technologies, different variant calling tools, and laborious manual curation. In this review, we discuss the available benchmark datasets and their utility. Additionally, we focus on the most recent benchmark of genes with medical relevance and challenging genomic complexity.
引用
收藏
页数:25
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