Browsing by Author "Chin, Chen-Shan"

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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.
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    Multiscale analysis of pangenomes enables improved representation of genomic diversity for repetitive and clinically relevant genes
    (Springer Nature, 2023) Chin, Chen-Shan; Behera, Sairam; Khalak, Asif; Sedlazeck, Fritz J.; Sudmant, Peter H.; Wagner, Justin; Zook, Justin M.
    Advancements in sequencing technologies and assembly methods enable the regular production of high-quality genome assemblies characterizing complex regions. However, challenges remain in efficiently interpreting variation at various scales, from smaller tandem repeats to megabase rearrangements, across many human genomes. We present a PanGenome Research Tool Kit (PGR-TK) enabling analyses of complex pangenome structural and haplotype variation at multiple scales. We apply the graph decomposition methods in PGR-TK to the class II major histocompatibility complex demonstrating the importance of the human pangenome for analyzing complicated regions. Moreover, we investigate the Y-chromosome genes, DAZ1/DAZ2/DAZ3/DAZ4, of which structural variants have been linked to male infertility, and X-chromosome genes OPN1LW and OPN1MW linked to eye disorders. We further showcase PGR-TK across 395 complex repetitive medically important genes. This highlights the power of PGR-TK to resolve complex variation in regions of the genome that were previously too complex to analyze.