Evidence map›Paper›PMID 41803952›Full record

ArticleGenome biology2026

Benchmarking Hi-C scaffolders using reference genomes and de novo assemblies.

Aakash Sur, William Stafford Noble, Peter J Myler

Abstract read
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

5 citing papers in PubMed.

  1. Chromosome-Level Genome Assembly and Annotation of theJournal of fungi (Basel, Switzerland) · 2026
    Article
  2. Article
  3. The Bioinformatic Applications of Hi-C and Linked Reads.Genomics, proteomics & bioinformatics · 2024
    Review
  4. Article
  5. Article
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.

Aakash SurDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, USA. asur@uw.edu.ORCID http://orcid.org/0000-0003-2946-0038
William Stafford NobleDepartment of Genome Sciences, University of Washington, Seattle, USA.
Peter J MylerDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, USA.ORCID http://orcid.org/0000-0002-0056-0513

Funding

Base J and transcription termination in LeishmaniaR01AI103858 · NIAID · SEATTLE CHILDREN'S HOSPITAL · PI MYLER, PETER JOHN · 2013 to 2017
$2.8M
Division of Intramural Research, National Institute of Allergy and Infectious Diseases 6R01AI103858-06NIAID NIH HHS R01 AI103858
6 · The paper itself

Abstract

backgroundStudying a new species using high-throughput sequencing requires a high-quality reference genome. However, assembling chromosome length sequences remains challenging. Recent advances in chromatin conformation capture (Hi-C) have provided a new approach to scaffolding genome assemblies, and the last ten years have seen a proliferation of such methods. However, to our knowledge no comprehensive benchmarking of Hi-C scaffolders has been conducted to date.

resultsThrough a literature review we identify the most popular Hi-C scaffolders - Lachesis, HiRise, 3d-dna, SALSA, and AllHiC. We test their ability to scaffold four well studied genomes - S. cerevisiae, L. tarentolae, A. thaliana, and H. sapiens. Scaffolders are tasked with both scaffolding fragmented versions of the reference genome as well as de novo assemblies derived from long read datasets. We find that all scaffolders can exceed 80% accuracy under ideal circumstances but that their performance quickly deteriorates under more challenging conditions. Surprisingly, many scaffolders also show poor performance on the best assemblies, where contigs are near chromosome length. Overall, we find that HiRise and Lachesis offer the best performance on average across all conditions.

conclusionsWe compare the performance of five Hi-C scaffolders using multiple reference species under both ideal and real-life conditions, thereby illuminating their strengths and weaknesses.

Indexed as

ChromatinGenomicsBenchmarkingHigh-Throughput Nucleotide SequencingHumansSaccharomyces cerevisiaeSequence Analysis, DNASoftwareChromatin

Identifiers

PMID41803952
PMCPMC13085270

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LicenceCC BY
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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.