Pique
Pique identifies peaks in high-coverage ChIP-seq data from bacterial and archaeal genomes to detect protein–DNA interactions and map regulatory elements.
Key Features:
- High-efficiency peak finding: Identifies peaks in high-coverage ChIP-seq experiments with emphasis on datasets from bacteria and archaea.
- Targeted for bacterial and archaeal data: Addresses challenges specific to prokaryotic ChIP-seq that can limit conventional eukaryote-focused peak callers.
- Implementation: Implemented as an open-source application written in Python.
- Standardized output formats: Produces outputs in standardized file formats for downstream analysis and tool interoperability.
- Integration with Gaggle Genome Browser: Outputs can be imported into the Gaggle Genome Browser for genome visualization and curation.
- Compatibility with R and graphics/statistics software: Output is compatible with R and other statistical/graphics software for downstream analysis and visualization.
- Open-source licensing: Distributed under the BSD-3 license with only freely licensed dependencies.
- Cross-platform compatibility: Runs across multiple operating systems.
Scientific Applications:
- Peak detection in prokaryotic ChIP-seq: Accurate identification of enrichment peaks in high-coverage ChIP-seq datasets from bacterial and archaeal samples.
- Protein–DNA interaction mapping: Detection of binding sites for DNA-associated proteins in prokaryotic genomes.
- Regulatory element discovery and gene regulation analysis: Support for locating regulatory elements and informing studies of gene expression mechanisms, with downstream analysis using R and genome browsers.
Methodology:
Implemented in Python and employs a tailored algorithmic approach to overcome limitations of existing peak finders on high-coverage bacterial and archaeal ChIP-seq data, minimizing errors and enhancing detection accuracy.
Topics
Details
- License:
- BSD-3-Clause
- Tool Type:
- command-line tool
- Programming Languages:
- Python
- Added:
- 1/9/2020
- Last Updated:
- 12/28/2020
Operations
Publications
Neches RY, Seitzer PM, Wilbanks EG, Facciotti MT. In a fit of pique: Analyzing microbial ChIP-Seq data with Pique. Unknown Journal. 2014. doi:10.7287/peerj.preprints.290v2.
Links
Repository
https://github.com/ryneches/piqueIssue tracker
https://github.com/ryneches/pique/issues