Igor Martayan

spearfish improves long-read mapping efficiency by leveraging transcriptome redundancy, achieving faster speeds and lower memory usage than existing tools.

This paper revisits the concept of density in k-mer-based sequence analysis, introduces multiminimizers as a novel technique, and proposes deduplicated density as a new metric.

The paper introduces K2Rmini, a tool that efficiently filters sequences based on k-mer matches, achieving 2 Gbp/s on a consumer laptop.

Helicase provides a fast, vectorized parser for FASTA/Q files, outperforming existing libraries by leveraging SIMD and efficient bitpacking.

The paper introduces a fast library for computing random minimizers using SIMD instructions, achieving significant speed improvements over existing methods.

This paper introduces Brisk, a resource-efficient k-mer dictionary that reduces memory usage and improves throughput compared to existing methods.

The paper introduces hyper-k-mers, a more efficient k-mer representation, and presents KFC, a tool that significantly reduces memory usage and improves speed for k-mer counting.

The paper introduces a framework to efficiently enumerate k-mers from a collection of references based on metadata constraints, using a specialized data structure and demonstrating it on microbial and RNA-seq data.

The paper introduces CBL, a dynamic and exact k-mer set representation that outperforms existing methods and supports in-place set operations.

This paper introduces a new sketching method for genomic data that reduces space and memory usage while maintaining efficiency and accuracy compared to existing tools.