MoMI-G: Modular Multi-scale Integrated Genome Graph Browser

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

doi:10.1101/540120

Cited by 4 publications

(4 citation statements)

References 72 publications

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“…For example, Bandage (Wick et al, 2015) allows the visualization of graph-based pangenomes without further inner details to be provided and adopted. Although SequenceTubeMaps (Beyer et al, 2019) and MoMi-G (Yokoyama et al, 2019) We have identified important genes and gene clusters underlying the indica-japonica differentiation using a rice graph pangenome and rice short read sequencing data, which demonstrated VAG can help discover biological stories hidden behind read alignment data using a graphical pangenome.…”

Section: Discussionmentioning

confidence: 99%

Visualization and review of reads alignment on the graphical pan-genome with VAG

Xiao

et al. 2023

Preprint

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Recent advances in pangenomics have led to the rapid development of graph based pangenomes that code genetic variant as nodes and edges preserve the contiguity of the sequence and structural variation between individuals. Data visualization is an essential component of genomic data analysis. However, the further application of the graph based pangenome is still suffered from lacking bioinformatics tools to visualize graph format pangenomes and understand the reads alignment on graph pangenomes. In this research, we developed a novel bioinformatics platform, VAG (Visualizing read alignments in graph genomes), to overcome these challenges. VAG includes multifunctional modules integrated into a single command line and an online visualization platform supported through a web server. This tool can extract specific sequence regions from a graph pangenome and display read alignments on different paths of a graph pangenome. In addition, VAG provides population level presence/absence variations frequency analysis and sequence path navigation to identify the population differentiation regions. To demonstrate the usage, we investigated genetic variations using a rice graph pangenome with population level sequencing data to identify important genes and gene clusters underlying the indica/japonica differentiation with VAG. After investigating read alignments on the graph pangenome, we identified many false/positive alignments due to TE insertions. To reduce the impact of these misleading alignments, we developed a navigation module to determine and filter those false/positive alignments based on the pair-end alignment information. The utilization of mate-pair information in VAG provides a reliable reference for variation identification. Additionally, we developed a VAG web server to provide a user-friendly and interactive platform to visualize the read alignment data. VAG was also applied to SV discovery in the cucumber and soybean graph-based pangenome and details of VAG can be accessed by the following website (https://ricegenomichjx.xiaomy.net/VAG/sequenceextraction.php).

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Section: Discussionmentioning

confidence: 99%

Visualization and review of reads alignment on the graphical pan-genome with VAG

Xiao

et al. 2023

Preprint

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“…Some of these tools include the Pan Genome Graph Builder (pggb)-a pan genome Graph construction pipeline to create a pangenome graph of multiple genome sequences (https://github.com/pangenome/pggb), the variation graph toolkit -vg, a collection of computational methods for efficient mapping of reads on variation graphs using generalized compressed suffix arrays (Hickey et al, 2020). Assembly and graph visualization tools are also available -these include MoMI-G or Modular Multi-scale Integrated Genome graph browser (Yokoyama et al, 2019), GraphAligner (Rautiainen and Marschall 2020), Pantograph (Chen et al, 2019) and GfaViz (Gonnella, Niehus, and Kurtz 2019), Sequence Tube Map (Beyer et al, 2019), Bandage (Wick et al, 2015) etc. To ensure quality control, Pan Genome Graph Evaluator selects the best pangenome graph construction (https://github.com/ pangenome/pgge).…”

Section: Toolsmentioning

confidence: 99%

From the reference human genome to human pangenome: Premise, promise and challenge

2022

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The Reference Human Genome remains the single most important resource for mapping genetic variations and assessing their impact. However, it is monophasic, incomplete and not representative of the variation that exists in the population. Given the extent of ethno-geographic diversity and the consequent diversity in clinical manifestations of these variations, population specific references were developed overtime. The dramatically plummeting cost of sequencing whole genomes and the advent of third generation long range sequencers allowing accurate, error free, telomere-to-telomere assemblies of human genomes present us with a unique and unprecedented opportunity to develop a more composite standard reference consisting of a collection of multiple genomes that capture the maximal variation existing in the population, with the deepest annotation possible, enabling a realistic, reliable and actionable estimation of clinical significance of specific variations. The Human Pangenome Project thus is a logical next step promising a more accurate and global representation of genomic variations. The pangenome effort must be reciprocally complemented with precise variant discovery tools and exhaustive annotation to ensure unambiguous clinical assessment of the variant in ethno-geographical context. Here we discuss a broad roadmap, the challenges and way forward in developing a universal pangenome reference including data visualization techniques and integration of prior knowledge base in the new graph based architecture and tools to submit, compare, query, annotate and retrieve relevant information from the pangenomes. The biggest challenge, however, will be the ethical, legal and social implications and the training of human resource to the new reference paradigm.

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“…Graph genomes can handle large, complex, and nested SVs more naturally than linear genomes, where SVs are represented as the differences from the reference genomes. MoMI-G [37] provides a graph-based visualization for SVs in human genomes and a customizable layout of view modules with circos plot, SV table, graph view, and linear genome browser. MoMI-G demonstrated that it was able to display nested SVs and a large SV of megabases with long-read alignments in an intuitive way.…”

Section: Graph Genome-based Sv Visualization Toolsmentioning

confidence: 99%

Visualization tools for human structural variations identified by whole-genome sequencing

Yokoyama

Kasahara

2019

J Hum Genet

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Visualizing structural variations (SVs) is a critical step for finding associations between SVs and human traits or diseases. Given that there are many sequencing platforms used for SV identification and given that how best to visualize SVs together with other data, such as read alignments and annotations, depends on research goals, there are dozens of SV visualization tools designed for different research goals and sequencing platforms. Here, we provide a comprehensive survey of over 30 SV visualization tools to help users choose which tools to use. This review targets users who wish to visualize a set of SVs identified from the massively parallel sequencing reads of an individual human genome. We first categorize the ways in which SV visualization tools display SVs into ten major categories, which we denote as view modules. View modules allow readers to understand the features of each SV visualization tool quickly. Next, we introduce the features of individual SV visualization tools from several aspects, including whether SV views are integrated with annotations, whether long-read alignment is displayed, whether underlying data structures are graph-based, the type of SVs shown, whether auditing is possible, whether bird's eye view is available, sequencing platforms, and the number of samples. We hope that this review will serve as a guide for readers on the currently available SV visualization tools and lead to the development of new SV visualization tools in the near future.

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MoMI-G: Modular Multi-scale Integrated Genome Graph Browser

Cited by 4 publications

References 72 publications

Visualization and review of reads alignment on the graphical pan-genome with VAG

Visualization and review of reads alignment on the graphical pan-genome with VAG

From the reference human genome to human pangenome: Premise, promise and challenge

Visualization tools for human structural variations identified by whole-genome sequencing

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