snakePipes

"snakePipes" is a comprehensive workflow package designed to facilitate the processing and downstream analysis of data derived from a variety of common epigenomic assays, including ChIP-seq, RNA-seq, Bisulfite-seq, ATAC-seq, Hi-C, and single-cell RNA-seq. It is specifically tailored to meet the demands for a modular and scalable approach to handle the complexity and expanding volume of epigenomic data in research.

Key Features and Functionalities:

- Modular Workflows for Epigenomic Assays: snakePipes provides pre-configured workflows for several epigenomic assays, enabling researchers to process and analyze data with precision and efficiency.

- Easy Installation and Upgrades: The package simplifies the installation of the underlying tools required for epigenomic data analysis. Users can easily install and upgrade snakePipes and its dependencies using Conda, a widely used package management system in bioinformatics.

- Flexible Workflow Assembly: Users can customize workflows to suit their research needs by assembling different workflow variants through command-line wrappers and YAML configuration files.

- Comprehensive Online Resources: snakePipes is supported by extensive documentation and a source code repository available online, providing users with the necessary guidance and resources for installation, configuration, and utilization of the package.

Topic

Epigenomics;ChIP-seq;RNA-Seq

Detail

  • Operation: -

  • Software interface: Command-line interface

  • Language: Python

  • License: The GNU General Public License v3.0

  • Cost: Free with restrictions

  • Version name: -

  • Credit: -

  • Input: -

  • Output: -

  • Contact: Devon P. Ryan ryan@ie-freiburg.mpg.de ,Thomas Manke manke@ie-freiburg.mpg.de

  • Collection: -

  • Maturity: Mature

Publications

  • snakePipes: facilitating flexible, scalable and integrative epigenomic analysis.
  • Bhardwaj V, et al. snakePipes: facilitating flexible, scalable and integrative epigenomic analysis. snakePipes: facilitating flexible, scalable and integrative epigenomic analysis. 2019; 35:4757-4759. doi: 10.1093/bioinformatics/btz436
  • https://doi.org/10.1093/BIOINFORMATICS/BTZ436
  • PMID: 31134269
  • PMC: PMC6853707

Download and documentation


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