K2R: Tinted de Bruijn graphs implementation for efficient read extraction from sequencing datasets.

ABSTRACT:

Summary

Biological sequence analysis often relies on reference genomes, but producing accurate assemblies remains a challenge. As a result, de novo analysis directly from raw reads, without preprocessing, is frequently more practical. A common task across many applications is to identify reads containing a given k-mer in a dataset-essential for genotyping, profiling, compression, error correction, and assembly. While this resembles the well-studied colored de Bruijn graph problem, solving it at the read level is typically too resource-intensive. We show that this challenge becomes tractable by making realistic assumptions about genome sequencing datasets. To address it, we introduce Tinted de Bruijn graphs, a variation of the colored de Bruijn graph in which each read is tre

SUBMITTER: Vandamme L 

PROVIDER: S-EPMC12257931 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature