Evidence map›Paper›PMID 38058196›Full record

ArticleBioinformatics (Oxford, England)2023

invMap: a sensitive mapping tool for long noisy reads with inversion structural variants.

Ze-Gang Wei, Peng-Yu Bu, Xiao-Dan Zhang, Fei Liu, Yu Qian, Fang-Xiang Wu

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ze-Gang WeiSchool of Physics and Optoelectronics Technology, Baoji University of Arts and Sciences, Baoji 721016, China.
Peng-Yu BuSchool of Physics and Optoelectronics Technology, Baoji University of Arts and Sciences, Baoji 721016, China.
Xiao-Dan ZhangSchool of Physics and Optoelectronics Technology, Baoji University of Arts and Sciences, Baoji 721016, China.
Fei LiuSchool of Physics and Optoelectronics Technology, Baoji University of Arts and Sciences, Baoji 721016, China.
Yu QianSchool of Physics and Optoelectronics Technology, Baoji University of Arts and Sciences, Baoji 721016, China.
Fang-Xiang WuDivision of Biomedical Engineering, Department of Computer Science and Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada.ORCID 0000-0002-4593-9332

Funding

22JSY021China Scholarship Council 202108615064Natural Science and Engineering Research Council of CanadaNatural Science Basic Research Plan in Shaanxi Province of China 2022JZ-03Shaanxi Fundamental Science ResearchShaanxi Provincial Education Department 23JK0287
6 · The paper itself

Abstract

motivationLonger reads produced by PacBio or Oxford Nanopore sequencers could more frequently span the breakpoints of structural variations (SVs) than shorter reads. Therefore, existing long-read mapping methods often generate wrong alignments and variant calls. Compared to deletions and insertions, inversion events are more difficult to be detected since the anchors in inversion regions are nonlinear to those in SV-free regions. To address this issue, this study presents a novel long-read mapping algorithm (named as invMap).

resultsFor each long noisy read, invMap first locates the aligned region with a specifically designed scoring method for chaining, then checks the remaining anchors in the aligned region to discover potential inversions. We benchmark invMap on simulated datasets across different genomes and sequencing coverages, experimental results demonstrate that invMap is more accurate to locate aligned regions and call SVs for inversions than the competing methods. The real human genome sequencing dataset of NA12878 illustrates that invMap can effectively find more candidate variant calls for inversions than the competing methods. AVAILABILITY AND IMPLEMENTATION: The invMap software is available at https://github.com/zhang134/invMap.git.

Indexed as

GenomicsHigh-Throughput Nucleotide SequencingAlgorithmsChromosome InversionGenome, HumanHumansSequence Analysis, DNASoftware

Identifiers

PMID38058196
PMCPMC11320709

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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.