Using SAAS-CNV to detect and characterize somatic copy number alterations in cancer genomes from next generation sequencing and SNP array data

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations

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.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages29-47
Number of pages19
DOIs
StatePublished - 2018

Publication series

NameMethods in Molecular Biology
Volume1833
ISSN (Print)1064-3745

Keywords

  • Cancer genome
  • Copy number variation
  • Next-generation sequencing
  • SAAS-CNV
  • SNP array
  • Segmentation
  • Somatic copy number alteration
  • Whole-exome sequencing
  • Whole-genome sequencing

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