Title
Multi-factor data normalization enables the detection of copy number aberrations in amplicon sequencing data.
Abstract
Motivation: Because of its low cost, amplicon sequencing, also known as ultra-deep targeted sequencing, is now becoming widely used in oncology for detection of actionable mutations, i.e. mutations influencing cell sensitivity to targeted therapies. Amplicon sequencing is based on the polymerase chain reaction amplification of the regions of interest, a process that considerably distorts the information on copy numbers initially present in the tumor DNA. Therefore, additional experiments such as single nucleotide polymorphism ( SNP) or comparative genomic hybridization (CGH) arrays often complement amplicon sequencing in clinics to identify copy number status of genes whose amplification or deletion has direct consequences on the efficacy of a particular cancer treatment. So far, there has been no proven method to extract the information on gene copy number aberrations based solely on amplicon sequencing. Results: Here we present ONCOCNV, a method that includes a multifactor normalization and annotation technique enabling the detection of large copy number changes from amplicon sequencing data. We validated our approach on high and low amplicon density datasets and demonstrated that ONCOCNV can achieve a precision comparable with that of array CGH techniques in detecting copy number aberrations. Thus, ONCOCNV applied on amplicon sequencing data would make the use of additional array CGH or SNP array experiments unnecessary.
Year
DOI
Venue
2014
10.1093/bioinformatics/btu436
BIOINFORMATICS
Keywords
Field
DocType
polymerase chain reaction,exome,comparative genomic hybridization,gene dosage
Massive parallel sequencing,Deep sequencing,Copy-number variation,Biology,Amplicon,Single cell sequencing,Comparative genomic hybridization,Bioinformatics,Genetics,Copy number analysis,Exome sequencing
Journal
Volume
Issue
ISSN
30
24
1367-4803
Citations 
PageRank 
References 
4
0.48
9
Authors
13