ArticleGenome biology2021
SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data.
Article in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
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- Integrated transcriptomic and physiological analysis reveals cadmium stress responses in kiwifruit rootstockFrontiers in plant science · 2026Article
- Evaluation of false positive and false negative errors in targeted next generation sequencing.Genome biology · 2025Article
- ConSeqUMI, an error-free nanopore sequencing pipeline to identify and extract individual nucleic acid molecules from heterogeneous samples.Nucleic acids research · 2025Article
- Clonal Evolution of Pediatric Acute Myeloid Leukemia and Its Contribution to Disease Relapse.medRxiv : the preprint server for health sciences · 2025Article
- Evaluation of Antioxidant Function of Palygorskite and Its Derivatives In Vitro and for Broilers.Antioxidants (Basel, Switzerland) · 2025Article
- How error correction affects polymerase chain reaction deduplication: A survey based on unique molecular identifier datasets of short reads.Quantitative biology (Beijing, China) · 2025Review
- Transcriptome analysis reveals that regulation network of the genes related to unique double flowers in tropical viviparous water lily.Scientific reports · 2025Article
- Integrated transcriptome and BSA-seq analysis identifies a novel QTL for Meloidogyne graminicola resistance in rice HuaHang31.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- A chromosome-levelActa pharmaceutica Sinica. B · 2025Article
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Authors and funding
19 authors.
Funding
Abstract
backgroundThere is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations.
resultsWe propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket.
conclusionsOur study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets.
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