# Exploiting uniqueness: seed-chain-extend alignment on elastic founder graphs

## TL;DR

This paper introduces a new sequence-to-graph alignment method using elastic founder graphs for efficient and accurate genomic analysis.

## Contribution

A complete seed-chain-extend workflow using indexable elastic founder graphs for scalable sequence-to-graph alignment.

## Key findings

- iEFGs enable linear-time exact searches for sequence alignment.
- The method scales to telomere-to-telomere human chromosomes.
- High-quality seeds are efficiently found, chained, and extended.

## Abstract

Sequence-to-graph alignment is a central challenge of computational pangenomics. To overcome the theoretical hardness of the problem, state-of-the-art tools use seed-and-extend or seed-chain-extend heuristics to alignment. We implement a complete seed-chain-extend alignment workflow based on indexable elastic founder graphs (iEFGs) that support linear-time exact searches unlike general graphs. We show how to construct iEFGs, find high-quality seeds, chain, and extend them at the scale of a telomere-to-telomere assembled human chromosome.

Our sequence-to-graph alignment tool and the scripts to replicate our experiments are available in https://github.com/algbio/SRFAligner.