ReviewBriefings in bioinformatics2026
Computational tools for tandem repeat detection using long-read sequencing.
Review in Briefings in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- A Deep Dive into Allium Satellite DNAs: Expansion and Characterization of theInternational journal of molecular sciences · 2026Article
- A comprehensive assessment of tandem repeat genotyping methods for Nanopore long-read genomes.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Tandem repeats (TRs) play essential roles in a variety of biological functions, and their abnormal expansions are significantly implicated in phenotypic variation and cause >60 human diseases. However, long TR regions cannot be reliably detected using short-read sequencing, and long-read sequencing enables accurate genome-wide detection of TRs. In recent years, various computational tools have been developed to detect and genotype TRs from long-read data. In this survey, we systematically categorize and review 39 computational tools designed for TR detection, visualization and functional interpretation. We discuss their strengths and limitations for TR detection from long-read sequencing data, highlighting current challenges and future directions to advance long-read TR detection methodologies.
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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.