ArticleBMC research notes2014
Comparison of insertion/deletion calling algorithms on human next-generation sequencing data.
Article in BMC research notes, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Synth4bench: generating synthetic data for benchmarking tumor-only somatic variant calling algorithms.Frontiers in bioinformatics · 2026Article
- Comparative evaluation of SNVs, indels, and structural variations detected with short- and long-read sequencing data.Human genome variation · 2024Article
- Extend the benchmarking indel set by manual review using the individual cell line sequencing data from the Sequencing Quality Control 2 (SEQC2) project.Scientific reports · 2024Article
- Screening the pathogenic causes of congenital cataract via whole exome sequencing technology in three families: Molecular genetics of congenital cataract.Molecular medicine reports · 2023Article
- Optimizing Insertion and Deletion Detection Using Next-Generation Sequencing in the Clinical Laboratory.The Journal of molecular diagnostics : JMD · 2022Article
- Genome sequencing-based coverage analyses facilitate high-resolution detection of deletions linked to phenotypes of gamma-irradiated wheat mutants.BMC genomics · 2022Article
- Tool evaluation for the detection of variably sized indels from next generation whole genome and targeted sequencing data.PLoS computational biology · 2022Article
- Direct comparison of circulating tumor DNA sequencing assays with targeted large gene panels.PloS one · 2022Article
- Comparison of seven SNP calling pipelines for the next-generation sequencing data of chickens.PloS one · 2022Article
- Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.Nature biotechnology · 2021Article
- Performance evaluation of pipelines for mapping, variant calling and interval padding, for the analysis of NGS germline panels.BMC bioinformatics · 2021Article
- Comparative genomics of white and opaque cell states supports an epigenetic mechanism of phenotypic switching in Candida albicans.G3 (Bethesda, Md.) · 2021Article
- Detailed evaluation of cancer sequencing pipelines in different microenvironments and heterogeneity levels.Turkish journal of biology = Turk biyoloji dergisi · 2021Article
- INDEL detection, the 'Achilles heel' of precise genome editing: a survey of methods for accurate profiling of gene editing induced indels.Nucleic acids research · 2020Review
- Genomic diversity affects the accuracy of bacterial single-nucleotide polymorphism-calling pipelines.GigaScience · 2020Article
- Accurate Tracking of the Mutational Landscape of Diploid Hybrid Genomes.Molecular biology and evolution · 2019Article
- NGSEP3: accurate variant calling across species and sequencing protocols.Bioinformatics (Oxford, England) · 2019Article
- Comprehensive evaluation and characterisation of short read general-purpose structural variant calling software.Nature communications · 2019Article
- Performance assessment of variant calling pipelines using human whole exome sequencing and simulated data.BMC bioinformatics · 2019Article
- PKD1 Duplicated regions limit clinical Utility of Whole Exome Sequencing for Genetic Diagnosis of Autosomal Dominant Polycystic Kidney Disease.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundInsertions/deletions (indels) are the second most common type of genomic variant and the most common type of structural variant. Identification of indels in next generation sequencing data is a challenge, and algorithms commonly used for indel detection have not been compared on a research cohort of human subject genomic data. Guidelines for the optimal detection of biologically significant indels are limited. We analyzed three sets of human next generation sequencing data (48 samples of a 200 gene target exon sequencing, 45 samples of whole exome sequencing, and 2 samples of whole genome sequencing) using three algorithms for indel detection (Pindel, Genome Analysis Tool Kit's UnifiedGenotyper and HaplotypeCaller).
resultsWe observed variation in indel calls across the three algorithms. The intersection of the three tools comprised only 5.70% of targeted exon, 19.52% of whole exome, and 14.25% of whole genome indel calls. The majority of the discordant indels were of lower read depth and likely to be false positives. When software parameters were kept consistent across the three targets, HaplotypeCaller produced the most reliable results. Pindel results did not validate well without adjustments to parameters to account for varied read depth and number of samples per run. Adjustments to Pindel's M (minimum support for event) parameter improved both concordance and validation rates. Pindel was able to identify large deletions that surpassed the length capabilities of the GATK algorithms.
conclusionsDespite the observed variability in indel identification, we discerned strengths among the individual algorithms on specific data sets. This allowed us to suggest best practices for indel calling. Pindel's low validation rate of indel calls made in targeted exon sequencing suggests that HaplotypeCaller is better suited for short indels and multi-sample runs in targets with very high read depth. Pindel allows for optimization of minimum support for events and is best used for detection of larger indels at lower read depths.
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