Evidence map›Paper›PMID 31433799›Full record

ArticlePLoS computational biology2019

Integrating Hi-C links with assembly graphs for chromosome-scale assembly.

Jay Ghurye, Arang Rhie, Brian P Walenz, Anthony Schmitt, Siddarth Selvaraj, Mihai Pop, Adam M Phillippy, Sergey Koren

Abstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 506 papers.

0numbers the graph read from it
0cells of the map it votes in
506citing 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

506 citing papers in PubMed.

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446 more citing papers are in PubMed but not listed here.

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

8 authors.

Jay GhuryeDepartment of Computer Science, University of Maryland, College Park, Maryland, United States of America.ORCID 0000-0003-1381-4081
Arang RhieGenome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America.ORCID 0000-0002-9809-8127
Brian P WalenzGenome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America.ORCID 0000-0001-8431-1428
Anthony SchmittArima Genomics, San Diego, California, United States of America.
Siddarth SelvarajArima Genomics, San Diego, California, United States of America.
Mihai PopDepartment of Computer Science, University of Maryland, College Park, Maryland, United States of America.ORCID 0000-0001-9617-5304
Adam M PhillippyGenome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America.ORCID 0000-0003-2983-8934
Sergey KorenGenome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America.ORCID 0000-0002-1472-8962

Funding

Algorithms and Software for the Assembly of Metagenomic DataR01AI100947 · NIAID · UNIV OF MARYLAND, COLLEGE PARK · PI POP, MIHAI · 2013 to 2025
$7.4M
Commercialization of a low-cost user-friendly DNA preparation kit that produces chromosome-span contiguity from conventional short-read sequencing​​ for a wide range of applicationsR44HG009584 · NHGRI · ARIMA GENOMICS, INC. · PI SELVARAJ, SIDDARTH · 2017 to 2018
$1.8M
NHGRI NIH HHS R44 HG009584NIAID NIH HHS R01 AI100947
6 · The paper itself

Abstract

Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA.

Indexed as

Genome, HumanAlgorithmsAnimalsChromosomes, HumanComputational BiologyComputer SimulationDatabases, Nucleic AcidGenomic LibraryGenomicsHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNASoftware

Identifiers

PMID31433799
PMCPMC6719893

What OpenQuestion holds

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LicenceCC0
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Registered trials

None linked

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.