Evidence map›Paper›PMID 32631227›Full record

ArticleBMC bioinformatics2020

Optical map guided genome assembly.

Miika Leinonen, Leena Salmela

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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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

10 citing papers in PubMed.

  1. Article
  2. Benchmarking of bioinformatics tools for the hybridComputational and structural biotechnology journal · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. An Overview of the Genetics and Genomics of theFrontiers in plant science · 2021
    Review
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

2 authors.

Miika LeinonenDepartment of Computer Science, Helsinki Institute for Information Technology, University of Helsinki, Pietari Kalmin katu 5, Helsinki, Finland.
Leena SalmelaDepartment of Computer Science, Helsinki Institute for Information Technology, University of Helsinki, Pietari Kalmin katu 5, Helsinki, Finland. leena.salmela@cs.helsinki.fi.ORCID http://orcid.org/0000-0002-0756-543X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe long reads produced by third generation sequencing technologies have significantly boosted the results of genome assembly but still, genome-wide assemblies solely based on read data cannot be produced. Thus, for example, optical mapping data has been used to further improve genome assemblies but it has mostly been applied in a post-processing stage after contig assembly.

resultsWe propose OPTICALKERMIT which directly integrates genome wide optical maps into contig assembly. We show how genome wide optical maps can be used to localize reads on the genome and then we adapt the Kermit method, which originally incorporated genetic linkage maps to the miniasm assembler, to use this information in contig assembly. Our experimental results show that incorporating genome wide optical maps to the contig assembly of miniasm increases NGA50 while the number of misassemblies decreases or stays the same. Furthermore, when compared to the Canu assembler, OPTICALKERMIT produces an assembly with almost three times higher NGA50 with a lower number of misassemblies on real A. thaliana reads.

conclusionsOPTICALKERMIT successfully incorporates optical mapping data directly to contig assembly of eukaryotic genomes. Our results show that this is a promising approach to improve the contiguity of genome assemblies.

Indexed as

GenomeHigh-Throughput Nucleotide SequencingHumansVoltage-Sensitive Dye ImagingGenome assemblyOptical mapping

Identifiers

PMID32631227
PMCPMC7336458

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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.