ArticleGenome biology2020
Performance difference of graph-based and alignment-based hybrid error correction methods for error-prone long reads.
Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- K-MARVEL: K-Mer-based antimicrobial resistance virtual exploration lab.Nature communications · 2026Article
- Precision medicine in liver transplantation for hepatocellular carcinoma: applications and prospects of third-generation sequencing technology.Journal of cancer research and clinical oncology · 2025Review
- Assembly collapsing versus heterozygosity oversizing: detection of homokaryotic and heterokaryoticMicrobial genomics · 2024Article
- AccuVIR: an ACCUrate VIRal genome assembly tool for third-generation sequencing data.Bioinformatics (Oxford, England) · 2023Article
- Full-length transcriptome sequencing reveals the molecular mechanism of potato seedlings responding to low-temperature.BMC plant biology · 2022Article
- The Statistics ofJournal of computational biology : a journal of computational molecular cell biology · 2022Article
- Performance difference of graph-based and alignment-based hybrid error correction methods for error-prone long reads.Genome biology · 2020Article
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
The error-prone third-generation sequencing (TGS) long reads can be corrected by the high-quality second-generation sequencing (SGS) short reads, which is referred to as hybrid error correction. We here investigate the influences of the principal algorithmic factors of two major types of hybrid error correction methods by mathematical modeling and analysis on both simulated and real data. Our study reveals the distribution of accuracy gain with respect to the original long read error rate. We also demonstrate that the original error rate of 19% is the limit for perfect correction, beyond which long reads are too error-prone to be corrected by these methods.
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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.