SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples.
10.1016/j.gpb.2020.02.003
- Author:
Yongzhe REN
1
,
2
;
Yang ZHANG
3
;
Dandan WANG
3
;
Fengying LIU
3
;
Ying FU
3
;
Shaohua XIANG
4
;
Li SU
5
;
Jiancheng LI
6
;
Heng DAI
3
;
Bingding HUANG
1
,
7
,
8
Author Information
1. (1)College of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China
2. (2)Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China.
3. (2)Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China.
4. (1)College of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.
5. (3)Department of Integrated Traditional and Western Medicine In Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.
6. (4)Department of Radiation Oncology, Fujian Medical University Cancer Hospital and Fujian Cancer Hospital, Fuzhou 350014, China.
7. (2)Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China
8. Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen 518005, China. Electronic address: huangbingding@sztu.edu.cn.
- Publication Type:Journal Article
- Keywords:
Circulating tumor DNA;
Duplex sequencing;
Liquid biopsy;
Low frequency variant;
Next generation sequencing
- From:
Genomics, Proteomics & Bioinformatics
2020;18(1):81-90
- CountryChina
- Language:English
-
Abstract:
Accurate detection of low frequency mutations from plasma cell-free DNA in blood using targeted next generation sequencing technology has shown promising benefits in clinical settings. Duplex sequencing technology is the most commonly used approach in liquid biopsies. Unique molecular identifiers are attached to each double-stranded DNA template, followed by production of low-error consensus sequences to detect low frequency variants. However, high sequencing costs have hindered application of this approach in clinical practice. Here, we have developed an improved duplex sequencing approach called SinoDuplex, which utilizes a pool of adapters containing pre-defined barcode sequences to generate far fewer barcode combinations than with random sequences, and implemented a novel computational analysis algorithm to generate duplex consensus sequences more precisely. SinoDuplex increased the output of duplex sequencing technology, making it more cost-effective. We evaluated our approach using reference standard samples and cell-free DNA samples from lung cancer patients. Our results showed that SinoDuplex has high sensitivity and specificity in detecting very low allele frequency mutations. The source code for SinoDuplex is freely available at https://github.com/SinOncology/sinoduplex.
