Comparative analysis of methods for identifying somatic copy number alterations from deep sequencing data

被引:40
作者
Alkodsi, Amjad [1 ,3 ]
Louhimo, Riku [1 ,3 ]
Hautaniemi, Sampsa [1 ,2 ]
机构
[1] Univ Helsinki, Syst Biol Lab, Res Programs Unit, Genome Scale Biol, FIN-00014 Helsinki, Finland
[2] Univ Helsinki, Fac Med, Syst Biol, FIN-00014 Helsinki, Finland
[3] Univ Helsinki, Inst Biomed, FIN-00014 Helsinki, Finland
基金
芬兰科学院;
关键词
Somatic copy number alterations; algorithm comparison; whole-genome sequencing; whole-exome sequencing; cancer; COMPARATIVE GENOMIC HYBRIDIZATION; HIGH-RESOLUTION ANALYSIS; READ ALIGNMENT; CANCER GENOME; HETEROZYGOSITY; ABERRATIONS; INTEGRATION; EXPRESSION; FRAMEWORK;
D O I
10.1093/bib/bbu004
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Somatic copy-number alterations (SCNAs) are an important type of structural variation affecting tumor pathogenesis. Accurate detection of genomic regions with SCNAs is crucial for cancer genomics as these regions contain likely drivers of cancer development. Deep sequencing technology provides single-nucleotide resolution genomic data and is considered one of the best measurement technologies to detect SCNAs. Although several algorithms have been developed to detect SCNAs from whole-genome and whole-exome sequencing data, their relative performance has not been studied. Here, we have compared ten SCNA detection algorithms in both simulated and primary tumor deep sequencing data. In addition, we have evaluated the applicability of exome sequencing data for SCNA detection. Our results show that (i) clear differences exist in sensitivity and specificity between the algorithms, (ii) SCNA detection algorithms are able to identify most of the complex chromosomal alterations and (iii) exome sequencing data are suitable for SCNA detection.
引用
收藏
页码:242 / 254
页数:13
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