ArticleScientific reports2017
Comparison of error correction algorithms for Ion Torrent PGM data: application to hepatitis B virus.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Prevalence of BRCA homopolymeric indels in an ION Torrent-based tumour-to-germline testing workflow in high-grade ovarian carcinoma.Scientific reports · 2023Article
- Single nucleotide variants of succinate dehydrogenase A gene in renal cell carcinoma.Cancer science · 2021Article
- Late Relapse and Reinfection in HCV Patients Treated with Direct-Acting Antiviral (DAA) Drugs.Viruses · 2021Article
- MIPP-Seq: ultra-sensitive rapid detection and validation of low-frequency mosaic mutations.BMC medical genomics · 2021Article
- Genome Evolution of Two Genetically Homogeneous Infectious Bursal Disease Virus Strains During PassagesFrontiers in microbiology · 2021Article
- Identification of Recurrent Mutations in the microRNA-Binding Sites of B-Cell Lymphoma-Associated Genes in Follicular Lymphoma.International journal of molecular sciences · 2020Article
- Microbiome Composition andTropical medicine and infectious disease · 2020Article
- Applying next-generation sequencing to unravel the mutational landscape in viral quasispecies.Virus research · 2020Review
- Article
- High-throughput sequencing for the molecular diagnosis of Usher syndrome reveals 42 novel mutations and consolidates CEP250 as Usher-like disease causative.Scientific reports · 2018Article
- Article
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6 authors.
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Abstract
Ion Torrent Personal Genome Machine (PGM) technology is a mid-length read, low-cost and high-speed next-generation sequencing platform with a relatively high insertion and deletion (indel) error rate. A full systematic assessment of the effectiveness of various error correction algorithms in PGM viral datasets (e.g., hepatitis B virus (HBV)) has not been performed. We examined 19 quality-trimmed PGM datasets for the HBV reverse transcriptase (RT) region and found a total error rate of 0.48% ± 0.12%. Deletion errors were clearly present at the ends of homopolymer runs. Tests using both real and simulated data showed that the algorithms differed in their abilities to detect and correct errors and that the error rate and sequencing depth significantly affected the performance. Of the algorithms tested, Pollux showed a better overall performance but tended to over-correct 'genuine' substitution variants, whereas Fiona proved to be better at distinguishing these variants from sequencing errors. We found that the combined use of Pollux and Fiona gave the best results when error-correcting Ion Torrent PGM viral data.
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