RT Journal Article
SR Electronic
T1 Unveiling Genomic Complexity: A Framework for Genome Graph Structural Analysis and Optimised Variant Calling Workflows
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2024.06.10.598220
DO 10.1101/2024.06.10.598220
A1 Kamaraj, Venkatesh
A1 Gupta, Ayam
A1 Narayanan, Manikandan
A1 Raman, Karthik
A1 Sinha, Himanshu
YR 2024
UL http://biorxiv.org/content/early/2024/06/11/2024.06.10.598220.abstract
AB Genome graphs have gained prominence and are becoming increasingly pertinent in the genomic research landscape. Despite their innate advantages, there is a shortage of techniques to comprehensively analyse the structural properties of genome graphs and systematically unearth the underlying genomic complexity of the population or species they represent. In this study, we formulated a novel framework to represent and capture the intricate structural complexities inherent in genome graphs. This approach opens up the opportunity to visualise the entire human genome at once and enables the prioritisation of sites of interest that are valuable for in-depth research. We applied the formulated technique to visualise and compare the structural properties of two human pan-genome graphs: one that augments only the variants commonly present in different human populations and the other that augments all the variants, including the rare ones. We also developed and benchmarked various genome-graph-based variant calling workflows and analysed human whole genomes with them. We compared the variant-calling performance of the two constructed graphs with each other and with the linear reference genome. We identified that genome graphs are better reference structures than their linear counterparts, and the proposed structural analysis framework can effectively analyse, visualise and compare the complexities embedded in them.Competing Interest StatementThe authors have declared no competing interest.