|Title||Genomic variant benchmark: if you cannot measure it, you cannot improve it.|
|Publication Type||Journal Article|
|Year of Publication||2023|
|Authors||Majidian, S, Agustinho, DPaiva, Chin, C-S, Sedlazeck, FJ, Mahmoud, M|
|Date Published||2023 Oct 05|
|Keywords||Benchmarking, Computational Biology, Genome, Genomics, High-Throughput Nucleotide Sequencing|
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.
|Alternate Journal||Genome Biol|
|PubMed Central ID||PMC10552390|
|Grant List||U01 HG011758 / HG / NHGRI NIH HHS / United States |
U19 AI144297 / AI / NIAID NIH HHS / United States
Genomic variant benchmark: if you cannot measure it, you cannot improve it.
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