GCsnap2 Cluster is a scalable, high performance tool for genomic context analysis, developed to overcome the limitations of its predecessor, GCsnap1 Desktop. Leveraging distributed computing with mpi4py[.]futures, GCsnap2 Cluster achieved a 22x improvement in execution time and can now perform genomic context analysis for hundreds of thousands of input sequences in HPC clusters. Its modular architecture enables the creation of task-specific workflows and flexible deployment in various computational environments, making it well suited for bioinformatics studies of large-scale datasets. This work highlights the potential for applying similar approaches to solve scalability challenges in other scientific domains that rely on large-scale data analysis pipelines.
@article{arxiv.2505.02195,
title = {Scalable Genomic Context Analysis with GCsnap2 on HPC Clusters},
author = {Reto Krummenacher and Osman Seckin Simsek and Michèle Leemann and Leila T. Alexander and Torsten Schwede and Florina M. Ciorba and Joana Pereira},
journal= {arXiv preprint arXiv:2505.02195},
year = {2025}
}
Comments
16 pages, 9 figures, 2 tables. Preprint submitted to arXiv