Academic Journal

Pangenome graph layout by Path-Guided Stochastic Gradient Descent

التفاصيل البيبلوغرافية
العنوان: Pangenome graph layout by Path-Guided Stochastic Gradient Descent
المؤلفون: Heumos, Simon, Guarracino, Andrea, Schmelzle, Jan-Niklas M, Li, Jiajie, Zhang, Zhiru, Hagmann, Jörg, Nahnsen, Sven, Prins, Pjotr, Garrison, Erik
المساهمون: Robinson, Peter, German Network for Bioinformatics Infrastructure, National Institutes of Health
المصدر: Bioinformatics ; volume 40, issue 7 ; ISSN 1367-4811
بيانات النشر: Oxford University Press (OUP)
سنة النشر: 2024
الوصف: Motivation The 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. 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, 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.
نوع الوثيقة: article in journal/newspaper
اللغة: English
DOI: 10.1093/bioinformatics/btae363
DOI: 10.1093/bioinformatics/btae363/58425532/btae363.pdf
الاتاحة: http://dx.doi.org/10.1093/bioinformatics/btae363
https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btae363/58425532/btae363.pdf
https://academic.oup.com/bioinformatics/article-pdf/40/7/btae363/58463786/btae363.pdf
Rights: https://creativecommons.org/licenses/by/4.0/
رقم الانضمام: edsbas.59EB92F2
قاعدة البيانات: BASE
الوصف
DOI:10.1093/bioinformatics/btae363