Evidence map›Paper›PMID 31690272›Full record

ArticleBMC bioinformatics2019

MoMI-G: modular multi-scale integrated genome graph browser.

Toshiyuki T Yokoyama, Yoshitaka Sakamoto, Masahide Seki, Yutaka Suzuki, Masahiro Kasahara

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Efficient indexing and querying of annotations in a pangenome graph.bioRxiv : the preprint server for biology · 2024
    Article
  10. Article
  11. Review
  12. Unbiased pangenome graphs.Bioinformatics (Oxford, England) · 2023
    Article
  13. Article
  14. ODGI: understanding pangenome graphs.Bioinformatics (Oxford, England) · 2022
    Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Pangenome Graphs.Annual review of genomics and human genetics · 2020
    Review
  20. 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

5 authors.

Toshiyuki T YokoyamaDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Yoshitaka SakamotoDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Masahide SekiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Yutaka SuzukiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Masahiro KasaharaDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan. mkasa@k.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0001-8430-1414

Funding

Japan Society for the Promotion of Science 16H06279
6 · The paper itself

Abstract

backgroundGenome graph is an emerging approach for representing structural variants on genomes with branches. For example, representing structural variants of cancer genomes as a genome graph is more natural than representing such genomes as differences from the linear reference genome. While more and more structural variants are being identified by long-read sequencing, many of them are difficult to visualize using existing structural variants visualization tools. To this end, visualization method for large genome graphs such as human cancer genome graphs is demanded.

resultsWe developed MOdular Multi-scale Integrated Genome graph browser, MoMI-G, a web-based genome graph browser that can visualize genome graphs with structural variants and supporting evidences such as read alignments, read depth, and annotations. This browser allows more intuitive recognition of large, nested, and potentially more complex structural variations. MoMI-G has view modules for different scales, which allow users to view the whole genome down to nucleotide-level alignments of long reads. Alignments spanning reference alleles and those spanning alternative alleles are shown in the same view. Users can customize the view, if they are not satisfied with the preset views. In addition, MoMI-G has Interval Card Deck, a feature for rapid manual inspection of hundreds of structural variants. Herein, we describe the utility of MoMI-G by using representative examples of large and nested structural variations found in two cell lines, LC-2/ad and CHM1.

conclusionsUsers can inspect complex and large structural variations found by long-read analysis in large genomes such as human genomes more smoothly and more intuitively. In addition, users can easily filter out false positives by manually inspecting hundreds of identified structural variants with supporting long-read alignments and annotations in a short time. SOFTWARE AVAILABILITY: MoMI-G is freely available at https://github.com/MoMI-G/MoMI-G under the MIT license.

Indexed as

Genome, HumanSoftwareWeb BrowserAllelesCell LineDiploidyGenomic Structural VariationHumansUser-Computer InterfaceGenome browserGenome graphsLong-read sequencingStructural variantVariation graphsVisualization

Identifiers

PMID31690272
PMCPMC6833150

What OpenQuestion holds

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LicenceCC BY
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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.