# Rawsamble: overlapping raw nanopore signals using a hash-based seeding mechanism

**Authors:** Can Firtina, Maximilian Mordig, Harun Mustafa, Sayan Goswami, Nika Mansouri Ghiasi, Stefano Mercogliano, Furkan Eris, Joel Lindegger, André Kahles, Onur Mutlu

PMC · DOI: 10.1093/bioinformatics/btag087 · 2026-02-26

## TL;DR

Rawsamble enables fast and memory-efficient genome assembly directly from raw nanopore signals without needing a reference genome or basecalling.

## Contribution

Rawsamble introduces a hash-based method for all-vs-all overlapping of raw nanopore signals, enabling de novo assembly without basecalling.

## Key findings

- Rawsamble provides a 5.01× average speedup and 5.74× lower memory usage compared to conventional pipelines.
- Unitigs built from Rawsamble overlaps are as accurate as those from minimap2 and can reach lengths of up to 2.3 million bases.
- Approximately one-third of Rawsamble’s overlaps match those found by minimap2.

## Abstract

Raw nanopore signal analysis is a common approach in genomics to provide fast and resource-efficient analysis without translating the signals to bases (i.e. without basecalling). However, existing solutions cannot interpret raw signals directly if a reference genome is unknown due to a lack of accurate mechanisms to handle increased noise in pairwise raw signal comparison. Our goal is to enable the direct analysis of raw signals without a reference genome. To this end, we propose Rawsamble, the first mechanism that can identify regions of similarity between all raw signal pairs, known as all-vs-all overlapping, using a hash-based search mechanism.

We use these overlaps to construct de novo assembly graphs with an existing assembler, miniasm, off-the-shelf. To our knowledge, these are the first de novo assemblies ever constructed directly from raw signals without basecalling. Our extensive evaluations across multiple genomes of varying sizes show that Rawsamble provides a significant speedup (on average by 5.01× and up to 23.10×) and reduces peak memory usage (on average by 5.74× and up to by 22.00×) compared to a conventional genome assembly pipeline using the state-of-the-art tools for basecalling (Dorado’s fastest mode) and overlapping (minimap2) on a CPU. We find that around one-third of Rawsamble’s overlapping pairs are also found by minimap2. We find that when we use overlapping reads from Rawsamble, we can construct unitigs that are (i) as accurate as those built from minimap2’s overlaps and (ii) up to half a chromosome in length (e.g. 2.3 million bases for E. coli).

Rawsamble is available at https://github.com/CMU-SAFARI/RawHash. We also provide the scripts to fully reproduce our results on our GitHub page.

## Full-text entities

- **Chemicals:** Flye (-)
- **Species:** Escherichia coli (E. coli, species) [taxon 562]

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12975284/full.md

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Source: https://tomesphere.com/paper/PMC12975284