Evidence map›Paper›PMID 34291293›Full record

ArticleNucleic acids research2021

Aberration-corrected ultrafine analysis of miRNA reads at single-base resolution: a k-mer lattice approach.

Xuan Zhang, Pengyao Ping, Gyorgy Hutvagner, Michael Blumenstein, Jinyan Li

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 43% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Xuan ZhangData Science Institute, University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia.ORCID 0000-0002-3089-9809
Pengyao PingData Science Institute, University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia.ORCID 0000-0002-1829-3273
Gyorgy HutvagnerSchool of Biomedical Engineering, Faculty of Engineering and IT, University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia.
Michael BlumensteinFaculty of Engineering and IT, University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia.
Jinyan LiData Science Institute, University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia.ORCID 0000-0003-1833-7413
University of Technology Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlgorithmsAnimalsComputational BiologyDatabases, GeneticHigh-Throughput Nucleotide SequencingHumansMicroRNAsSalmonSequence Analysis, DNAMicroRNAs

Identifiers

PMID34291293
PMCPMC8631080
OpenAlexW3185132034

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.