Abstract
Motivation The increasing availability of complete genomes demands for models to study genomic variability within entire populations. Pangenome graphs capture the full genetic diversity between multiple genomes, but their layouts may exhibit complex structures due to common, nonlinear patterns of genome variation and evolution. These structures hamper downstream analyses, visualization, and interpretation.
Results In 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, to move pairs of nodes in parallel applying a modified HOGWILD! strategy. We show that our implementation efficiently computes the layout of gigabase-scale pangenome graphs, unveiling their biological features.
Availability 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.
Contact egarris5{at}uthsc.edu
Competing Interest Statement
Author J.H. is employed by Computomics GmbH.
Footnotes
↵† The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.
https://github.com/human-pangenomics/hpp_pangenome_resources#pggb
