Evidence map›Paper›PMID 31289833›Full record

ArticleGigaScience2019

OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps.

Alden King-Yung Leung, Melissa Chun-Jiao Liu, Le Li, Yvonne Yuk-Yin Lai, Catherine Chu, Pui-Yan Kwok, Pak-Leung Ho, Kevin Y Yip, Ting-Fung Chan

Abstract read
In one paragraph

Article in GigaScience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Advances in optical mapping for genomic research.Computational and structural biotechnology journal · 2020
    Review
  3. 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

9 authors.

Alden King-Yung LeungSchool of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong.
Melissa Chun-Jiao LiuCarol Yu Center for Infection and Department of Microbiology, The University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong.
Le LiDepartment of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong.
Yvonne Yuk-Yin LaiCardiovascular Research Institute, University of California, San Francisco, CA 94153, USA.
Catherine ChuCardiovascular Research Institute, University of California, San Francisco, CA 94153, USA.
Pui-Yan KwokCardiovascular Research Institute, University of California, San Francisco, CA 94153, USA.
Pak-Leung HoCarol Yu Center for Infection and Department of Microbiology, The University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong.
Kevin Y YipDepartment of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong.
Ting-Fung ChanSchool of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong.

Funding

Single molecule DNA mapping for genome and CNV analysisR01HG005946 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KWOK, PUI-YAN, XIAO, MING · 2010 to 2021
$6.5M
NHGRI NIH HHS R01 HG005946
6 · The paper itself

Abstract

backgroundOptical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping analysis involve assembling optical maps into contigs and aligning them to a reference, which is limited to pairwise comparison and becomes bias-prone when analyzing multiple samples.

findingsWe present a new method, OMMA, that extends optical mapping to the study of complex genomic features by simultaneously interrogating optical maps across many samples in a reference-independent manner. OMMA captures and characterizes complex genomic features, e.g., multiple haplotypes, copy number variations, and subtelomeric structures when applied to 154 human samples across the 26 populations sequenced in the 1000 Genomes Project. For small genomes such as pathogenic bacteria, OMMA accurately reconstructs the phylogenomic relationships and identifies functional elements across 21 Acinetobacter baumannii strains.

conclusionsWith the increasing data throughput of optical mapping system, the use of this technology in comparative genome analysis across many samples will become feasible. OMMA is a timely solution that can address such computational need. The OMMA software is available at https://github.com/TF-Chan-Lab/OMTools.

Indexed as

Polymorphism, GeneticSoftwareGenome, HumanGenomicsHumansOptical Restriction MappingPhylogenyPopulationSequence Analysis, DNAcomparative genomicscopy number variationhaplotypesoptical mappingsingle-molecule analysisstructural variation

Identifiers

PMID31289833
PMCPMC6615982

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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.