Scalable Genomic Context Analysis with GCsnap2 on HPC Clusters

TL;DR

GCsnap2 Cluster is a high-performance, scalable tool for genomic context analysis that leverages distributed computing to handle large datasets efficiently in HPC environments.

Contribution

It introduces GCsnap2 Cluster, a scalable, modular tool that significantly improves execution time for genomic analysis on HPC clusters compared to its predecessor.

Findings

22x reduction in execution time

Can analyze hundreds of thousands of sequences

Flexible deployment in various environments

Abstract

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.