RawAlign: Accurate, Fast, and Scalable Raw Nanopore Signal Mapping via Combining Seeding and Alignment

TL;DR

RawAlign is a novel method that combines seeding and alignment to achieve accurate, fast, and scalable mapping of raw nanopore signals, especially for large genomes, outperforming existing tools in accuracy and efficiency.

Contribution

RawAlign introduces the first integration of fine-grained signal alignment into raw nanopore signal mapping, with algorithmic improvements and hardware acceleration for enhanced performance.

Findings

Achieves the most accurate mapping for large genomes.

Performs comparably to RawHash, with slight variations.

Outperforms UNCALLED and Sigmap by significant margins.

Abstract

Nanopore sequencers generate raw electrical signals representing the contents of a biological sequence molecule passing through the nanopore. These signals can be analyzed directly, avoiding basecalling entirely. We observe that while existing proposals for raw signal analysis typically do well in all metrics for small genomes (e.g., viral genomes), they all perform poorly for large genomes (e.g., the human genome). Our goal is to analyze raw nanopore signals in an accurate, fast, and scalable manner. To this end, we propose RawAlign, the first work to integrate fine-grained signal alignment into the state-of-the-art raw signal mapper. To enable accurate, fast, and scalable mapping with alignment, RawAlign implements three algorithmic improvements and hardware acceleration via a vectorized implementation of fine-grained alignment. Together, these significantly reduce the overhead of typically computationally expensive fine-grained alignment. Our extensive evaluations on different use cases and various datasets show RawAlign provides 1) the most accurate mapping for large genomes and 2) and on-par performance compared to RawHash (between 0.80x-1.08x), while achieving better performance than UNCALLED and Sigmap by on average (geo. mean) 2.83x and 2.06x, respectively. Availability: https://github.com/CMU-SAFARI/RawAlign.