Browsing by Author "Agustinho, Daniel Paiva"

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    Genomic variant benchmark: if you cannot measure it, you cannot improve it
    (Springer Nature, 2023) Majidian, Sina; Agustinho, Daniel Paiva; Chin, Chen-Shan; Sedlazeck, Fritz J.; Mahmoud, Medhat
    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.