ArticleBioinformatics (Oxford, England)2024
Pangenome graph layout by Path-Guided Stochastic Gradient Descent.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- PangyPlot: multi-scale interactive visualization of pangenome variation graphs.Bioinformatics (Oxford, England) · 2026Article
- Gretl-variation GRaph Evaluation TooLkit.Bioinformatics (Oxford, England) · 2024Article
- Cluster-efficient pangenome graph construction with nf-core/pangenome.Bioinformatics (Oxford, England) · 2024Article
- Efficient indexing and querying of annotations in a pangenome graph.bioRxiv : the preprint server for biology · 2024Article
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9 authors.
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Abstract
motivationThe increasing availability of complete genomes demands for models to study genomic variability within entire populations. Pangenome graphs capture the full genomic similarity and diversity between multiple genomes. In order to understand them, we need to see them. For visualization, we need a human-readable graph layout: a graph embedding in low (e.g. two) dimensional depictions. Due to a pangenome graph's potential excessive size, this is a significant challenge.
resultsIn response, we introduce a novel graph layout algorithm: the Path-Guided Stochastic Gradient Descent (PG-SGD). PG-SGD uses the genomes, represented in the pangenome graph as paths, as an embedded positional system to sample genomic distances between pairs of nodes. This avoids the quadratic cost seen in previous versions of graph drawing by SGD. We show that our implementation efficiently computes the low-dimensional layouts of gigabase-scale pangenome graphs, unveiling their biological features. AVAILABILITY AND IMPLEMENTATION: We integrated PG-SGD in ODGI which is released as free software under the MIT open source license. Source code is available at https://github.com/pangenome/odgi.
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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.