PAPerFly: Partial Assembly-based Peak Finder for ab initio binding site reconstruction

0579941 - ÚOCHB 2024 RIV GB eng J - Journal Article
Faltejsková, Kateřina - Vondrášek, Jiří
PAPerFly: Partial Assembly-based Peak Finder for ab initio binding site reconstruction.
BMC Bioinformatics. Roč. 24, č. 1 (2023), č. článku 487. ISSN 1471-2105. E-ISSN 1471-2105
R&D Projects: GA MŠMT(CZ) EF16_019/0000729
Research Infrastructure: e-INFRA CZ - 90140
Institutional support: RVO:61388963
Keywords : ChIP-seq * DNA recognition * transcription factor * peak analysis * algorithm * graph theory
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 3, year: 2022
Method of publishing: Open access
https://doi.org/10.1186/s12859-023-05613-5

Background: The specific recognition of a DNA locus by a given transcription factor is a widely studied issue. It is generally agreed that the recognition can be influenced not only by the binding motif but by the larger context of the binding site. In this work, we present a novel heuristic algorithm that can reconstruct the unique binding sites captured in a sequencing experiment without using the reference genome. Results: We present PAPerFly, the Partial Assembly-based Peak Finder, a tool for the binding site and binding context reconstruction from the sequencing data without any prior knowledge. This tool operates without the need to know the reference genome of the respective organism. We employ algorithmic approaches that are used during genome assembly. The proposed algorithm constructs a de Bruijn graph from the sequencing data. Based on this graph, sequences and their enrichment are reconstructed using a novel heuristic algorithm. The reconstructed sequences are aligned and the peaks in the sequence enrichment are identified. Our approach was tested by processing several ChIP-seq experiments available in the ENCODE database and comparing the results of Paperfly and standard methods. Conclusions: We show that PAPerFly, an algorithm tailored for experiment analysis without the reference genome, yields better results than an aggregation of ChIP-seq agnostic tools. Our tool is freely available at https://github.com/Caeph/paperfly/ or on Zenodo (https://doi.org/10.5281/zenodo.7116424).
Permanent Link: https://hdl.handle.net/11104/0348738