PANOMIQ: A Unified Approach to Whole-Genome, Exome, and Microbiome Data Analysis

Abstract

The integration of whole-genome sequencing (WGS), whole-exome sequencing (WES), and microbiome analysis has become essential for advancing our understanding of complex biological systems. However, the fragmented nature of current analytical tools often complicates the process, leading to inefficiencies and potential data loss. To address this challenge, we present PANOMIQ, a comprehensive software solution that unifies the analysis of WGS, WES, and microbiome data into a single, streamlined pipeline. PANOMIQ is designed to facilitate the entire analysis process from raw data to interpretable results. It is the fastest algorithm that can achieve results much more quickly compared to traditional pipeline approaches of WGS and WES analysis. It incorporates advanced algorithms for high-accuracy variant calling in both WGS and WES, along with robust tools for characterizing microbial communities. The software's modular architecture allows for seamless integration of these diverse data types, enabling researchers to uncover complex interactions between host genomics and microbiomes. In this study, we demonstrate the capabilities of PANOMIQ by applying it to a series of datasets encompassing a wide range of applications, including disease association studies and environmental microbiome profiling. Our results highlight PANOMIQ's ability to deliver comprehensive insights, significantly reducing the time and computational resources required for multi-omic analysis. By providing a unified platform for WGS, WES, and microbiome analysis, PANOMIQ offers a powerful tool for researchers aiming to explore the full spectrum of genomic and microbial diversity. This software not only simplifies the analytical workflow but also enhances the depth of biological interpretation, paving the way for more integrated and holistic studies in genomics and microbiology.