Evidence map›Paper›PMID 40181468›Full record

ArticleMobile DNA2025

REPrise: de novo interspersed repeat detection using inexact seeding.

Atsushi Takeda, Daisuke Nonaka, Yuta Imazu, Tsukasa Fukunaga, Michiaki Hamada

Abstract read
In one paragraph

Article in Mobile DNA, 2025. 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

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

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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. 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

5 authors.

Atsushi Takeda *Department of Electrical Engineering and Bioscience, Graduate School of Advanced Science and Engineering, Waseda University, Tokyo, 1698555, Japan.
Daisuke Nonaka *Department of Computer Science, Graduate School of Information Science and Technology, the University of Tokyo, Tokyo, 1130032, Japan.
Yuta ImazuDepartment of Electrical Engineering and Bioscience, School of Advanced Science and Engineering, Waseda University, Tokyo, 1698555, Japan.
Tsukasa FukunagaDepartment of Computer Science, Graduate School of Information Science and Technology, the University of Tokyo, Tokyo, 1130032, Japan. fukunaga@aoni.waseda.jp.
Michiaki HamadaDepartment of Electrical Engineering and Bioscience, Graduate School of Advanced Science and Engineering, Waseda University, Tokyo, 1698555, Japan. mhamada@waseda.jp.

Funding

Japan Agency for Medical Research and Development JP22ama121055Japan Society for the Promotion of Science 22H04925Japan Society for the Promotion of Science JP23K16997Japan Society for the Promotion of Science JP23KJ2044
6 · The paper itself

Abstract

backgroundInterspersed repeats occupy a large part of many eukaryotic genomes, and thus their accurate annotation is essential for various genome analyses. Database-free de novo repeat detection approaches are powerful for annotating genomes that lack well-curated repeat databases. However, existing tools do not yet have sufficient repeat detection performance.

resultsIn this study, we developed REPrise, a de novo interspersed repeat detection software program based on a seed-and-extension method. Although the algorithm of REPrise is similar to that of RepeatScout, which is currently the de facto standard tool, we incorporated three unique techniques into REPrise: inexact seeding, affine gap scoring and loose masking. Analyses of rice and simulation genome datasets showed that REPrise outperformed RepeatScout in terms of sensitivity, especially when the repeat sequences contained many mutations. Furthermore, when applied to the complete human genome dataset T2T-CHM13, REPrise demonstrated the potential to detect novel repeat sequence families.

conclusionREPrise can detect interspersed repeats with high sensitivity even in long genomes. Our software enhances repeat annotation in diverse genomic studies, contributing to a deeper understanding of genomic structures.

Indexed as

De novo repeat detectionInexact seedREPriseSeed-and-extend

Identifiers

PMID40181468
PMCPMC11966803

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.