Genomic variant benchmark: if you cannot measure it, you cannot improve it
Abstract 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 a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-10-01
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| Series: | Genome Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13059-023-03061-1 |
| _version_ | 1797452422407258112 |
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| author | Sina Majidian Daniel Paiva Agustinho Chen-Shan Chin Fritz J. Sedlazeck Medhat Mahmoud |
| author_facet | Sina Majidian Daniel Paiva Agustinho Chen-Shan Chin Fritz J. Sedlazeck Medhat Mahmoud |
| author_sort | Sina Majidian |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-09T15:08:32Z |
| format | Article |
| id | doaj.art-1bc6af0582274f8cae57dd03721502a5 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-03-09T15:08:32Z |
| publishDate | 2023-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-1bc6af0582274f8cae57dd03721502a52023-11-26T13:29:30ZengBMCGenome Biology1474-760X2023-10-0124112510.1186/s13059-023-03061-1Genomic variant benchmark: if you cannot measure it, you cannot improve itSina Majidian0Daniel Paiva Agustinho1Chen-Shan Chin2Fritz J. Sedlazeck3Medhat Mahmoud4Department of Computational Biology, University of LausanneBaylor College of Medicine, Human Genome Sequencing CenterSema4 OpCo, Inc.Baylor College of Medicine, Human Genome Sequencing CenterBaylor College of Medicine, Human Genome Sequencing CenterAbstract 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.https://doi.org/10.1186/s13059-023-03061-1Genetic variationSNPsIndelsStructural variantBenchmark datasetsMedical genes |
| spellingShingle | Sina Majidian Daniel Paiva Agustinho Chen-Shan Chin Fritz J. Sedlazeck Medhat Mahmoud Genomic variant benchmark: if you cannot measure it, you cannot improve it Genome Biology Genetic variation SNPs Indels Structural variant Benchmark datasets Medical genes |
| title | Genomic variant benchmark: if you cannot measure it, you cannot improve it |
| title_full | Genomic variant benchmark: if you cannot measure it, you cannot improve it |
| title_fullStr | Genomic variant benchmark: if you cannot measure it, you cannot improve it |
| title_full_unstemmed | Genomic variant benchmark: if you cannot measure it, you cannot improve it |
| title_short | Genomic variant benchmark: if you cannot measure it, you cannot improve it |
| title_sort | genomic variant benchmark if you cannot measure it you cannot improve it |
| topic | Genetic variation SNPs Indels Structural variant Benchmark datasets Medical genes |
| url | https://doi.org/10.1186/s13059-023-03061-1 |
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