NDLI: Analysis of computational footprinting methods for DNase sequencing experiments.

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Analysis of computational footprinting methods for DNase sequencing experiments.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Gusmao, Eduardo G. Allhoff, Manuel Zenke, Martin Costa, Ivan G.
Description	Country affiliation: Germany Author Affiliation: Gusmao EG ( IZKF Computational Biology Research Group, RWTH Aachen University Medical School, Aachen, Germany.); Allhoff M ( Department of Cell Biology, Institute of Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany.); Zenke M ( IZKF Computational Biology Research Group, RWTH Aachen University Medical School, Aachen, Germany.); Costa IG ( Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, Aachen, Germany.)
Abstract	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 DNase-seq 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.
File Format	HTM / HTML
ISSN	15487091
Issue Number	4
Volume Number	13
e-ISSN	15487105
Journal	Nature Methods
Language	English
Publisher	Nature Publishing Group
Publisher Date	2016-04-01
Publisher Place	United States
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discipline Clinical Laboratory Techniques Computational Biology Methods Dna Footprinting High-throughput Nucleotide Sequencing Sequence Analysis, Dna Software Transcription Factors Metabolism Algorithms Binding Sites Chromatin Genetics Chromatin Immunoprecipitation Deoxyribonuclease I Humans K562 Cells Protein Binding Journal Article Research Support, Non-u.s. Gov't
Content Type	Text
Resource Type	Article
Subject	Cell Biology Biochemistry Molecular Biology Biotechnology

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High-resolution mapping of in vivo genomic transcription factor binding sites using in situ DNase I footprinting and ChIP-seq.

DNase I footprinting.

Footprints by deep sequencing.

Streaming fragment assignment for real-time analysis of sequencing experiments.

Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors.

High-resolution mapping of transcription factor binding sites on native chromatin.

Coupling transcription factor occupancy to nucleosome architecture with DNase-FLASH.

Genomic footprinting.

Reproducible inference of transcription factor footprints in ATAC-seq and DNase-seq datasets via protocol-specific bias modeling

Analysis of computational footprinting methods for DNase sequencing experiments.

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High-resolution mapping of in vivo genomic transcription factor binding sites using in situ DNase I footprinting and ChIP-seq.

DNase I footprinting.

Footprints by deep sequencing.

Streaming fragment assignment for real-time analysis of sequencing experiments.

Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors.

High-resolution mapping of transcription factor binding sites on native chromatin.

Coupling transcription factor occupancy to nucleosome architecture with DNase-FLASH.

Genomic footprinting.

Reproducible inference of transcription factor footprints in ATAC-seq and DNase-seq datasets via protocol-specific bias modeling

Analysis of computational footprinting methods for DNase sequencing experiments.