Detecting common regions and overlaps between DNA sequences is crucial in many Bioinformatics tasks. One of them is genome assembly based on the use of the overlap graph which is constructed by detecting the overlap between genomic reads. When dealing with long reads this task is further complicated by the length of the reads and the high sequencing error rate. This paper proposes a novel alignment-free method for detecting the overlaps in a set of long reads which exploits a signature (called fingerprint) of reads built from a factorization of the read based on the notion of Lyndon words. The method has been implemented in the tool KFinger and tested over a simulated and a real PacBio HiFi dataset of genomic reads; its results have been compared with the well-known aligner Minimap2. KFinger is available at https://github.com/AlgoLab/kfinger.
KFinger: Capturing Overlaps Between Long Reads by Using Lyndon Fingerprints
Zaccagnino R.;Zizza R.
2022
Abstract
Detecting common regions and overlaps between DNA sequences is crucial in many Bioinformatics tasks. One of them is genome assembly based on the use of the overlap graph which is constructed by detecting the overlap between genomic reads. When dealing with long reads this task is further complicated by the length of the reads and the high sequencing error rate. This paper proposes a novel alignment-free method for detecting the overlaps in a set of long reads which exploits a signature (called fingerprint) of reads built from a factorization of the read based on the notion of Lyndon words. The method has been implemented in the tool KFinger and tested over a simulated and a real PacBio HiFi dataset of genomic reads; its results have been compared with the well-known aligner Minimap2. KFinger is available at https://github.com/AlgoLab/kfinger.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
