NoPeak: k-mer-based motif discovery in ChIP-Seq data without peak calling

• Published in: Bioinformatics Vol. 37; no. 5; pp. 596 - 602
• Main Authors: Menzel, Michael, Hurka, Sabine, Glasenhardt, Stefan, Gogol-Döring, Andreas
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 05.05.2021
• ISSN: 1367-4803; 1367-4811; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btaa845

Abstract Motivation The discovery of sequence motifs mediating DNA-protein binding usually implies the determination of binding sites using high-throughput sequencing and peak calling. The determination of peaks, however, depends strongly on data quality and is susceptible to noise. Results Here, we present a novel approach to reliably identify transcription factor-binding motifs from ChIP-Seq data without peak detection. By evaluating the distributions of sequencing reads around the different k-mers in the genome, we are able to identify binding motifs in ChIP-Seq data that yield no results in traditional pipelines. Availability and implementation NoPeak is published under the GNU General Public License and available as a standalone console-based Java application at https://github.com/menzel/nopeak. Supplementary information Supplementary data are available at Bioinformatics online.