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Using SAAS-CNV to Detect and Characterize Somatic Copy Number Alterations in Cancer Genomes from Next Generation Sequencing and SNP Array Data.

Author information

Affiliations

  • 1. Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
      Authors
    • Zhang Z 1
    • Hao K 1
    (2 authors)

Methods in Molecular Biology (Clifton, N.J.), 01 Jan 2018, 1833:29-47
https://doi.org/10.1007/978-1-4939-8666-8_2 PMID: 30039361 

Review

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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Read article at publisher's site: https://doi.org/10.1007/978-1-4939-8666-8_2

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