Pérez, EduardoNiestroj, LisaMartínez, MiguelVillaman, CamiloIrem, ElifLal, DennisMata, Ignacio2023-03-312023-03-312022Copy number variation analysis from SNP genotyping microarrays in large cohorts of neurological disorders. Eduardo Pérez-Palma, Lisa-Marie Niestroj, Miguel Inca-Martínez, Camilo Villaman, Elif Irem Sarihan, Dennis Lal, Ignacio Mata. Book Chapter. Neuromethods. Springer Nature. DOI: 10.1007/978-1-0716-2357-2_10https://repositorio.udd.cl/handle/11447/7227Copy number variants (CNVs) are a major source of genetic variation in the human genome, and they are highly heterogeneous in type, size, and frequency. CNVs represent the largest portion of genomic variation between humans, and a subset of CNVs has been associated with multiple rare and common neurological disorders. Although recent sequencing-based methods deliver increased resolution and greater power in detecting CNVs, SNP genotyping microarrays still provide a scalable opportunity to analyze CNVs in large cohorts of neurological disorders. In the past 15 years, case-control genome-wide association studies and population-based biobanks have widely used SNP genotyping microarrays to understand the heritability of common variants. As a result, massive amounts of SNP microarray data are available and provide a costefficient opportunity to repurpose the data and study large and rare CNVs. Here we describe a workflow to detect and analyze CNVs from SNP genotyping microarrays. We describe established CNV quality control procedures, CNV downstream analyses, case-control burden analysis, and validation protocols with particular focus on nervous system disorders and non-European datasets.enCopy number variationCNVsGenotypingStructural variationNeurological disordersGWASBook chapterhttps://doi.org/10.1007/978-1-0716-2357-2_10