Evidence map›Paper›PMID 30367582›Full record

ArticleBMC genomics2018

An improved approach for reconstructing consensus repeats from short sequence reads.

Chong Chu, Jingwen Pei, Yufeng Wu

Abstract readEvaluation Study
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

2 citing papers in PubMed.

  1. A draft genome assembly for the dart-poison frogGigaByte (Hong Kong, China) · 2025
    Article
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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

3 authors.

Chong ChuDepartment of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, 02115, MA, USA.
Jingwen PeiDepartment of Computer Science and Engineering, University of Connecticut, 371 Fairfield Way, Unit 2155, Storrs, 06269, CT, USA.
Yufeng WuDepartment of Computer Science and Engineering, University of Connecticut, 371 Fairfield Way, Unit 2155, Storrs, 06269, CT, USA. yufeng.wu@uconn.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRepeat elements are important components of most eukaryotic genomes. Most existing tools for repeat analysis rely either on high quality reference genomes or existing repeat libraries. Thus, it is still challenging to do repeat analysis for species with highly repetitive or complex genomes which often do not have good reference genomes or annotated repeat libraries. Recently we developed a computational method called REPdenovo that constructs consensus repeat sequences directly from short sequence reads, which outperforms an existing tool called RepARK. One major issue with REPdenovo is that it doesn't perform well for repeats with relatively high divergence rates or low copy numbers. In this paper, we present an improved approach for constructing consensus repeats directly from short reads. Comparing with the original REPdenovo, the improved approach uses more repeat-related k-mers and improves repeat assembly quality using a consensus-based k-mer processing method.

resultsWe compare the performance of the new method with REPdenovo and RepARK on Human, Arabidopsis thaliana and Drosophila melanogaster short sequencing data. And the new method fully constructs more repeats in Repbase than the original REPdenovo and RepARK, especially for repeats of higher divergence rates and lower copy number. We also apply our new method on Hummingbird data which doesn't have a known repeat library, and it constructs many repeat elements that can be validated using PacBio long reads.

conclusionWe propose an improved method for reconstructing repeat elements directly from short sequence reads. The results show that our new method can assemble more complete repeats than REPdenovo (and also RepARK). Our new approach has been implemented as part of the REPdenovo software package, which is available for download at https://github.com/Reedwarbler/REPdenovo .

Indexed as

Repetitive Sequences, Nucleic AcidAlgorithmsAnimalsArabidopsisBase SequenceBirdsConsensus SequenceDNADrosophila melanogasterHumansSequence AlignmentSequence Analysis, DNADNADe novo genome assemblyRepeat elementsSequence analysis

Identifiers

PMID30367582
PMCPMC6101065

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Registered trials

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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.