Comparative genome analysis using sample-specific string detection in accurate long reads

Abstract Motivation Comparative genome analysis of two or more whole-genome sequenced (WGS) samples is at the core of most applications in genomics. These include discovery of genomic differences segregating in population, case-control analysis in common diseases, and rare disorders. With the current progress of accurate long-read sequencing technologies (e.g., circular consensus sequencing from PacBio sequencers) we can dive into studying repeat regions of genome (e.g., segmental duplications) and hard-to-detect variants (e.g., complex structural variants). Results We propose a novel framework for addressing the comparative genome analysis by discovery of strings that are specific to one genome (“samples-specific” strings). We have developed an accurate and efficient novel method for discovery of samples-specific strings between two groups of WGS samples. The proposed approach will give us the ability to perform comparative genome analysis without the need to map the reads and is not hindered by shortcomings of the reference genome. We show that the proposed approach is capable of accurately finding samples-specific strings representing nearly all variation (> 98%) reported across pairs or trios of WGS samples using accurate long reads (e.g., PacBio HiFi data). Availability The proposed tool is publicly available at https://github.com/Parsoa/PingPong.