ArticleBioinformatics (Oxford, England)2019
A new statistic for efficient detection of repetitive sequences.
Article in Bioinformatics (Oxford, England), 2019. 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, 10 citations in OpenAlex.
- T2T-CHM13 reference genome reduces mapping bias and enhances alignment accuracy at disease-associated variants.iScience · 2026Article
- Complete Chloroplast Genome Sequences of ThreeCurrent issues in molecular biology · 2025Article
- First Complete Mitochondrial Genome Analysis of Tree Frog,International journal of molecular sciences · 2025Article
- Molecular Characterization and Phylogenetic Analysis of Centipedegrass [Current issues in molecular biology · 2024Article
- Genomic sequence capture of Plasmodium relictum in experimentally infected birds.Parasites & vectors · 2022Article
- BigFiRSt: A Software Program Using Big Data Technique for Mining Simple Sequence Repeats From Large-Scale Sequencing Data.Frontiers in big data · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
motivationDetecting sequences containing repetitive regions is a basic bioinformatics task with many applications. Several methods have been developed for various types of repeat detection tasks. An efficient generic method for detecting most types of repetitive sequences is still desirable. Inspired by the excellent properties and successful applications of the D2 family of statistics in comparative analyses of genomic sequences, we developed a new statistic D2R that can efficiently discriminate sequences with or without repetitive regions.
resultsUsing the statistic, we developed an algorithm of linear time and space complexity for detecting most types of repetitive sequences in multiple scenarios, including finding candidate clustered regularly interspaced short palindromic repeats regions from bacterial genomic or metagenomics sequences. Simulation and real data experiments show that the method works well on both assembled sequences and unassembled short reads. AVAILABILITY AND IMPLEMENTATION: The codes are available at https://github.com/XuegongLab/D2R_codes under GPL 3.0 license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
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.