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1.
Bioinformatics ; 37(5): 596-602, 2021 05 05.
Article in English | MEDLINE | ID: mdl-32991679

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.


Subject(s)
Chromatin Immunoprecipitation Sequencing , High-Throughput Nucleotide Sequencing , Binding Sites , Chromatin Immunoprecipitation , Sequence Analysis, DNA
2.
PeerJ Comput Sci ; 5: e198, 2019.
Article in English | MEDLINE | ID: mdl-33816851

ABSTRACT

The rise of high-throughput methods in genomic research greatly expanded our knowledge about the functionality of the genome. At the same time, the amount of available genomic position data increased massively, e.g., through genome-wide profiling of protein binding, virus integration or DNA methylation. However, there is no specialized software to investigate integration site profiles of virus integration or transcription factor binding sites by correlating the sites with the diversity of available genomic annotations. Here we present Enhort, a user-friendly software tool for relating large sets of genomic positions to a variety of annotations. It functions as a statistics based genome browser, not focused on a single locus but analyzing many genomic positions simultaneously. Enhort provides comprehensive yet easy-to-use methods for statistical analysis, visualization, and the adjustment of background models according to experimental conditions and scientific questions. Enhort is publicly available online at enhort.mni.thm.de and published under GNU General Public License.

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