ChIPseqR

ChIPseqR analyzes ChIP-seq data to identify nucleosome positions and histone modification patterns for high-resolution mapping of protein–DNA interactions and chromatin architecture.


Key Features:

  • Versatility: Adapts its model to analyze nucleosome positioning and other ChIP-seq experimental targets beyond transcription factor binding sites.
  • High sensitivity and resolution: Improves sensitivity and spatial resolution for more precise identification of protein binding sites and nucleosome locations.
  • Specificity maintenance: Preserves high specificity in predictions despite increased sensitivity.
  • Comprehensive nucleosome analysis: Facilitates exploration of characteristic patterns in nucleosome sequences and placement to inform chromatin structure studies.
  • Histone modification support: Handles histone modification ChIP-seq data explicitly.
  • Data types and robustness: Processes high-throughput short-read ChIP-seq sequencing data and performs robust analysis on simulated datasets.

Scientific Applications:

  • Protein–DNA interaction mapping: Provides high-resolution maps of protein binding sites and nucleosome positions in genomic studies.
  • Epigenetic research: Analyzes histone modification patterns to study influences on gene expression and chromatin architecture.
  • Nucleosome dynamics and positioning: Investigates nucleosome placement and dynamics across organisms, including analyses on Arabidopsis thaliana mononucleosomes.
  • Chromatin sequence-pattern analysis: Enables examination of characteristic sequence and placement patterns of nucleosomes genome-wide.

Methodology:

Processes high-throughput ChIP-seq short-read sequencing data and simulated datasets to analyze nucleosome positioning and histone modifications.

Topics

Collections

Details

License:
GPL-2.0
Tool Type:
command-line tool, library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
1/17/2017
Last Updated:
12/30/2018

Operations

Data Inputs & Outputs

Publications

Humburg P, Helliwell CA, Bulger D, Stone G. ChIPseqR: analysis of ChIP-seq experiments. BMC Bioinformatics. 2011;12(1). doi:10.1186/1471-2105-12-39. PMID:21281468. PMCID:PMC3045301.

Documentation

Downloads