Nucleosome Positioning


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Nucleosome Positioning

NuCMap | Nucleosome positioning : Epigenomics

Maps directly nucleosome centers. NuCMap is based on chemical modification of engineered histones. It locates nucleosome positions genome-wide on a map in unprecedented detail and accuracy and shows significantly stronger dinucleotide signals in nucleosome DNAs than MNase maps. The tool reveals novel aspects of the in vivo nucleosome organization that are linked to transcription factor (TF) binding, RNA polymerase pausing, and the higher order structure of the chromatin fiber.

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Institutions(s):

Department of Molecular Biosciences and Department of Chemistry, Northwestern University, Evanston, IL, USA; Department of Statistics, Northwestern University, Evanston, IL, USA


nuMap | Nucleosome positioning : Epigenomics

Implements the YR and W/S schemes to predict nucleosome positioning at high resolution. This methodology is based on the sequence-dependent anisotropic bending, which dictates how DNA is wrapped around a histone octamer. nuMap allows users to specify a number of options such as schemes and parameters for threading calculation and provides multiple layout formats.

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Institutions(s):

Thomas H Gosnell School of Life Sciences, Chinahester Institute of Technology, Rochester, NY, USA


ICM | Interactive Chromatin Modeling

Allows users to assess nucleosome stability and fold sequences of DNA into putative chromatin templates. ICM generates a nucleosome energy level diagram, coarse-grained representations of free DNA and chromatin and plots of the helical parameters (Tilt, Roll, Twist, Shift, Slide and Rise) as a function of position. It uses an elastic model to automatically place nucleosomes. The tool can be used to y assemble models of chromatin that can be employed to rationalize biophysical data, especially spatial relations.

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Institutions(s):

Department of Biostatistics, Tulane University, New Orleans, LA, USA; Centre for Computational Science, Lindy Boggs Centre, Tulane University, New Orleans, LA, USA

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MNase-seq analysis

The technology of micrococcal nuclease (MNase) digestion combined with high-throughput sequencing (MNase-seq) is a powerful method to map the genome-wide distribution of nucleosome occupancy (Mavrich et al., 2008; Schones et al., 2008; Jiang and Pugh, 2009). Source text: Chen et al., 2014.

PING

Serves for nucleosome positioning. PING uses MNase-Seq data or MNase - or sonicated - ChIP-Seq data combined with either single-end or paired-end sequencing. It enables nucleosome predictions even in the presence of low read counts. It contains functions for pre-processing and reading raw data. It can handle sonicated and MNase protocols combined with either single-end (SE) or paired-end (PE) sequencing.

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Documentation

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Institutions(s):

Vaccine and Infectious Diseases and Public Health Sciences Divisions, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA;


nucleR

A package for non-parametric nucleosome positioning. nucleR uses a novel aproach in this field which comprises a deep profile cleaning using Fourier Transform and peak scoring for a quick and flexible nucleosome calling.

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Institutions(s):

IRB-BSC Joint Research Program on Computational Biology, Institute of Research in Biomedicine, Barcelona, Spain


NOrMAL

A command line tool for accurate placing of the nucleosomes. NOrMAL was designed to resolve overlapping nucleosomes and extract extra information (“fuzziness”, probability, etc.) of nucleosome placement.

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Institutions(s):

Department of Computer Science and Engineering, University of California, Riverside, CA, USA

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ATAC-seq analysis

ATAC-seq allows simultaneous interrogation of factor occupancy, nucleosome positions in regulatory sites, and chromatin accessibility genome wide by considering the position of insertion and the distribution of insert lengths captured during the transposition reaction.

NucleoATAC | Nucleosome positionning analysis : ATAC-seq analysis

A python package for nucleosome-positioning using as basis the highly structured pattern of DNA fragment lengths and positions around nucleosomes. NucleoATAC can identify the rotational and translational positions of nucleosomes with up to base-pair resolution and provide quantitative measures of nucleosome occupancy in Schizosaccharomyces cerevisiae, Schizosaccharomyces pombe and human cells. NucleoATAC can be used to analyze sequence features underlying nucleosome positioning, to promote chromatin architecture across species, to identify transient changes in nucleosome occupancy and to asses positioning during a dynamic cellular response.

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Documentation

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Institutions(s):

Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA; Biophysics Program, Stanford University School of Medicine, Stanford, CA, USA; Department of Applied Physics, Stanford University, Stanford, CA, USA

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