Computational Biology
@ Comenius University in Bratislava

Alessia Petescia, Luca Denti, Askar Gafurov, Viktoria Hodorova, Jozef Nosek, Brona Brejova, Tomas Vinar. Alignment-free detection of differences between sequencing datasets. iScience, 28(11):113828. 2025.

Download preprint: not available

Download from publisher: not available

Related web page: not available

Bibliography entry: BibTeX

Abstract:

Comparing biological samples through sequencing is a core task in bioinformatics 
analyses such as variant detection, differential expression analysis, and 
epigenetic peak calling. Standard approaches typically rely on mapping newly 
sequenced reads to a reference genome. To avoid mapping and reference biases, 
k-mer-based approaches have been proposed as an alternative. Using this paradigm, 
our tool kdiff identifies genomic regions containing k-mers with differential 
abundances between samples. We demonstrate that our method effectively detects 
copy number variants in cancer genomes and remains robust against reference 
genome misassemblies. Additionally, we illustrate its utility in confirming 
telomere locations in noisy nanopore sequencing data. Our work demonstrates that 
alignment-free approaches can provide results comparable to standard 
alignment-based methods, while reducing the reference bias and significantly 
improving computational efficiency by leveraging fast k-mer counting tools.