INDELseek: detection of complex insertions and deletions from next-generation sequencing data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-01-05

AUTHORS

Chun Hang Au, Anskar Y. H. Leung, Ava Kwong, Tsun Leung Chan, Edmond S. K. Ma

ABSTRACT

BackgroundComplex insertions and deletions (indels) from next-generation sequencing (NGS) data were prone to escape detection by currently available variant callers as shown by large-scale human genomics studies. Somatic and germline complex indels in key disease driver genes could be missed in NGS-based genomics studies.ResultsINDELseek is an open-source complex indel caller designed for NGS data of random fragments and PCR amplicons. The key differentiating factor of INDELseek is that each NGS read alignment was examined as a whole instead of “pileup” of each reference position across multiple alignments. In benchmarking against the reference material NA12878 genome (n = 160 derived from high-confidence variant calls), GATK, SAMtools and INDELseek showed complex indel detection sensitivities of 0%, 0% and 100%, respectively. INDELseek also detected all known germline (BRCA1 and BRCA2) and somatic (CALR and JAK2) complex indels in human clinical samples (n = 8). Further experiments validated all 10 detected KIT complex indels in a discovery cohort of clinical samples. In silico semi-simulation showed sensitivities of 93.7–96.2% based on 8671 unique complex indels in >5000 genes from dbSNP and COSMIC. We also demonstrated the importance of complex indel detection in accurately annotating BRCA1, BRCA2 and TP53 mutations with gained or rescued protein-truncating effects.ConclusionsINDELseek is an accurate and versatile tool for complex indel detection in NGS data. It complements other variant callers in NGS-based genomics studies targeting a wide spectrum of genetic variations. More... »

PAGES

16

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12864-016-3449-9

DOI

http://dx.doi.org/10.1186/s12864-016-3449-9

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https://app.dimensions.ai/details/publication/pub.1039146636

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28056804


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