NoPeak: k-mer-based motif discovery in ChIP-Seq data without peak calling
Michael Menzel1, Sabine Hurka2, Stefan Glasenhardt1
1MNI, Technische Hochschule Mittelhessen, University of Applied Sciences, Giessen 35390, Germany.
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.
