ArticleNucleic acids research2021
Aberration-corrected ultrafine analysis of miRNA reads at single-base resolution: a k-mer lattice approach.
Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- PARiS: Probabilistic Assignment and Repartitioning of isomiR Sequences: A data-driven method for denoising isomiR read count data.bioRxiv : the preprint server for biology · 2026Article
- How error correction affects polymerase chain reaction deduplication: A survey based on unique molecular identifier datasets of short reads.Quantitative biology (Beijing, China) · 2025Review
- Charting the equine miRNA landscape: An integrated pipeline and browser for annotating, quantifying, and visualizing expression.PLoS genetics · 2025Article
- MicroRNAs in long COVID: roles, diagnostic biomarker potential and detection.Human genomics · 2025Review
- Intra-Host Co-Existing Strains of SARS-CoV-2 Reference Genome Uncovered by Exhaustive Computational Search.Viruses · 2023Article
- A curated human cellular microRNAome based on 196 primary cell types.GigaScience · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Raw sequencing reads of miRNAs contain machine-made substitution errors, or even insertions and deletions (indels). Although the error rate can be low at 0.1%, precise rectification of these errors is critically important because isoform variation analysis at single-base resolution such as novel isomiR discovery, editing events understanding, differential expression analysis, or tissue-specific isoform identification is very sensitive to base positions and copy counts of the reads. Existing error correction methods do not work for miRNA sequencing data attributed to miRNAs' length and per-read-coverage properties distinct from DNA or mRNA sequencing reads. We present a novel lattice structure combining kmers, (k - 1)mers and (k + 1)mers to address this problem. The method is particularly effective for the correction of indel errors. Extensive tests on datasets having known ground truth of errors demonstrate that the method is able to remove almost all of the errors, without introducing any new error, to improve the data quality from every-50-reads containing one error to every-1300-reads containing one error. Studies on experimental miRNA sequencing datasets show that the errors are often rectified at the 5' ends and the seed regions of the reads, and that there are remarkable changes after the correction in miRNA isoform abundance, volume of singleton reads, overall entropy, isomiR families, tissue-specific miRNAs, and rare-miRNA quantities.
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