Complex 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.INDELseek 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 (nā€‰=ā€‰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 (nā€‰=ā€‰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.INDELseek 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.


  1. INDELseek: detection of complex insertions and deletions from next-generation sequencing data.
    Cite this
    Au CH, Leung AY, Kwong A, Chan TL, Ma ES, 2017-01-01 - BMC genomics


  1. Chun Hang Au

    Division of Molecular Pathology, Department of Pathology, China

  2. Anskar Y H Leung

    Department of Medicine, The University of Hong Kong

  3. Ava Kwong

    Hong Kong Hereditary Breast Cancer Family Registry, Shau Kei Wan

  4. Tsun Leung Chan

    Division of Molecular Pathology, Department of Pathology, China

  5. Edmond S K Ma

    Division of Molecular Pathology, Department of Pathology, China

Community Ratings

UsabilityEfficiencyReliabilityRated By
0 user
Sign in to rate
Tool TypeApplication
User InterfaceTerminal Command Line
Download Count0
Submitted ByEdmond S K Ma