使用XCAVATOR和EXCAVATOR2从全基因组测序（WGS）、全外显子组测序（WES）和转录组测序（TS）数据中识别拷贝数变异（CNV）。

Using XCAVATOR and EXCAVATOR2 to Identify CNVs from WGS, WES, and TS Data.

作者信息

D'Aurizio Romina, Semeraro Roberto, Magi Alberto

机构信息

Institute of Informatics and Telematics, National Research Council, Pisa, Italy.

Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.

出版信息

Curr Protoc Hum Genet. 2018 Jul;98(1):e65. doi: 10.1002/cphg.65. Epub 2018 Jul 5.

DOI:10.1002/cphg.65

PMID:29975818

Abstract

Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation but also associated with many disease states. In recent years, the identification of CNVs from high-throughput sequencing experiments has become a common practice for both research and clinical purposes. Several computational methods have been developed so far. In this unit, we describe and give instructions on how to run two read count-based tools, XCAVATOR and EXCAVATOR2, which are tailored for the detection of both germline and somatic CNVs from different sequencing experiments (whole-genome, whole-exome, and targeted) in various disease contexts and population genetic studies. © 2018 by John Wiley & Sons, Inc.

摘要

拷贝数变异（CNV）是导致表型变异的结构重排，同时也与许多疾病状态相关。近年来，从高通量测序实验中识别CNV已成为研究和临床目的的常见做法。到目前为止，已经开发了几种计算方法。在本单元中，我们描述并给出了如何运行两种基于读取计数的工具XCAVATOR和EXCAVATOR2的说明，这两种工具专为在各种疾病背景和群体遗传学研究中从不同测序实验（全基因组、全外显子组和靶向测序）中检测种系和体细胞CNV而设计。© 2018约翰威立父子公司版权所有。