Abstract
Somatic copy number alterations (SCNAs) are profound in cancer genomes at different stages: oncogenesis, progression, and metastasis. Accurate detection and characterization of SCNA landscape at genome-wide scale are of great importance. Next-generation sequencing and SNP array are current technology of choice for SCNA analysis. They are able to quantify SCNA with high resolution and meanwhile raise great challenges in data analysis. To this end, we have developed an R package saasCNV for SCNA analysis using (1) whole-genome sequencing (WGS), (2) whole-exome sequencing (WES) or (3) whole-genome SNP array data. In this chapter, we provide the features of the package and step-by-step instructions in detail.
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Zhang, Z., Hao, K. (2018). Using SAAS-CNV to Detect and Characterize Somatic Copy Number Alterations in Cancer Genomes from Next Generation Sequencing and SNP Array Data. In: Bickhart, D. (eds) Copy Number Variants. Methods in Molecular Biology, vol 1833. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8666-8_2
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DOI: https://doi.org/10.1007/978-1-4939-8666-8_2
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