Journal
NATURE METHODS
Volume 13, Issue 4, Pages 303-309Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.3772
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Funding
- Interdisciplinary Center for Clinical Research (IZKF Aachen), RWTH Aachen University Medical School, Aachen, Germany
- Excellence Initiative of the German Federal Government
- Excellence Initiative of the German State Government
- German Research Foundation [GSC 111]
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DNase-seq allows nucleotide-level identification of transcription factor binding sites on the basis of a computational search of footprint-like DNase I cleavage patterns on the DNA. Frequently in high-throughput methods, experimental artifacts such as DNase I cleavage bias affect the computational analysis of DNase-seq experiments. Here we performed a comprehensive and systematic study on the performance of computational footprinting methods. We evaluated ten footprinting methods in a panel of DNaseseq experiments for their ability to recover cell-specific transcription factor binding sites. We show that three methods HINT, DNase2TF and PIQ-consistently outperformed the other evaluated methods and that correcting the DNase-seq signal for experimental artifacts significantly improved the accuracy of computational footprints. We also propose a score that can be used to detect footprints arising from transcription factors with potentially short residence times.
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