CODEX2: full-spectrum copy number variation detection by high-throughput DNA sequencing

被引：41

作者：

Jiang, Yuchao ^{[1
,2
,3
]}

Wang, Rujin ^{[1
]}

Urrutia, Eugene ^{[1
]}

Anastopoulos, Ioannis N. ^{[4
]}

Nathanson, Katherine L. ^{[4
,5
]}

Zhang, Nancy R. ^{[6
]}

机构：

[1] Univ N Carolina, Dept Biostat, Gillings Sch Global Publ Hlth, Chapel Hill, NC 27599 USA

[2] Univ N Carolina, Dept Genet, Sch Med, Chapel Hill, NC 27599 USA

[3] Univ N Carolina, Lineberger Comprehens Canc Ctr, Chapel Hill, NC 27599 USA

[4] Univ Penn, Dept Med, Div Translat Med & Human Genet, Perelman Sch Med, Philadelphia, PA 19104 USA

[5] Univ Penn, Perelman Sch Med, Abramson Canc Ctr, Philadelphia, PA 19104 USA

[6] Univ Penn, Wharton Sch, Dept Stat, Philadelphia, PA 19104 USA

来源：

GENOME BIOLOGY | 2018年 / 19卷

基金：

美国国家卫生研究院;

关键词：

Copy number variation; Normalization; Next-generation sequencing; Latent factor; Negative control; DISCOVERY; VARIANTS; COMMON; GENES;

D O I：

10.1186/s13059-018-1578-y

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

High-throughput DNA sequencing enables detection of copy number variations (CNVs) on the genome-wide scale with finer resolution compared to array-based methods but suffers from biases and artifacts that lead to false discoveries and low sensitivity. We describe CODEX2, as a statistical framework for full-spectrum CNV profiling that is sensitive for variants with both common and rare population frequencies and that is applicable to study designs with and without negative control samples. We demonstrate and evaluate CODEX2 on whole-exome and targeted sequencing data, where biases are the most prominent. CODEX2 outperforms existing methods and, in particular, significantly improves sensitivity for common CNVs.

引用

页数：13

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