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

Author:

Menzel Michael1,Hurka Sabine2ORCID,Glasenhardt Stefan1,Gogol-Döring Andreas1

Affiliation:

1. MNI, Technische Hochschule Mittelhessen, University of Applied Sciences, Giessen 35390, Germany

2. Institute for Insect Biotechnology, Justus Liebig University, Giessen 35392, Germany

Abstract

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.

Funder

Research Campus of Central Hessen

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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