GeNePi: a graphics processing unit enhanced next-generation bioinformatics pipeline for whole-genome sequencing analysis

Abstract

Next-generation sequencing (NGS) has revolutionized genome biology by enabling rapid whole-genome sequencing (WGS) and driving its adoption in research and clinical settings. However, the high-throughput nature of NGS and the complexity of downstream analyses demand robust computational solutions. We present GeNePi, a modular bioinformatic pipeline for efficient and accurate analysis of WGS short paired-end reads. GeNePi is a genomics analysis pipeline built on the Nextflow framework, integrating graphics processing unit (GPU)-accelerated algorithms from NVIDIA Clara Parabricks to enable high-performance variant discovery. The pipeline supports multiple workflow configurations and automates the detection of a broad range of genomic variants, including single-nucleotide variants and small insertions/deletions via GPU-accelerated HaplotypeCaller, copy number variants (CNVs) using CNVkit, and structural variants through a consensus approach combining Manta, Lumpy, BreakDancer, and CNVnator. Additionally, GeNePi incorporates MELT for the detection of mobile element insertions, providing a comprehensive framework for variant discovery and characterization. Benchmarking on synthetic and real datasets demonstrates high accuracy and performance comparable to state-of-the-art tools such as Genome Analysis ToolKit (GATK), establishing GeNePi as a scalable solution for comprehensive WGS analysis. These features make GeNePi a valuable instrument for large-scale analyses in both research and clinical contexts, representing a key step towards the establishment of National Centers for Computational and Technological Medicine.