Majidian, SinaAgustinho, Daniel PaivaChin, Chen-ShanSedlazeck, Fritz J.Mahmoud, Medhat2024-05-032024-05-032023Majidian, S., Agustinho, D. P., Chin, C.-S., Sedlazeck, F. J., & Mahmoud, M. (2023). Genomic variant benchmark: If you cannot measure it, you cannot improve it. Genome Biology, 24(1), 221. https://doi.org/10.1186/s13059-023-03061-1https://hdl.handle.net/1911/115600Genomic 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.engExcept where otherwise noted, this work is licensed under a Creative Commons Attribution (CC BY) license. Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Journal articles13059-023-03061-1https://doi.org/10.1186/s13059-023-03061-1