greenPipes: an integrated data analysis pipeline for greenCUT&RUN and CUT&RUN genome-localization datasets

Bioinformatics. 2024 May 2;40(5):btae307. doi: 10.1093/bioinformatics/btae307.

Abstract

Motivation: To study gene regulation through transcription factors and chromatin modifiers, a variety of genome-wide techniques are used. Recently, CUT&RUN-based technologies have become popular, but a pipeline for the comprehensive analysis of CUT&RUN datasets is currently lacking. Here, we present the "greenPipes" package, which includes fine-tuned parameters specifically for bioinformatic analyses of greenCUT&RUN and CUT&RUN datasets. greenPipes provides additional functionalities for data analysis and data integration with other -omics technologies, which are either not available in other pipelines developed for CUT&RUN datasets or scattered in the literature as individual packages.

Availability and implementation: Source code and a manual of the greenPipes are freely available on GitHub website (https://github.com/snizam001/greenPipes). The test datasets, comprehensive annotation files, and other datasets are available at https://osf.io/ruhj9/.

Contact: n.sheikh@dkfz-heidelberg.de or m.timmers@dkfz-heidelberg.de.

Supplementary information: The handbook of greenPipes is available online at Bioinformatics as Supplementary text.

MeSH terms

  • Chromatin / chemistry
  • Chromatin / metabolism
  • Computational Biology* / methods
  • Databases, Genetic
  • Genome
  • Genomics / methods
  • Humans
  • Software*
  • Transcription Factors / metabolism

Substances

  • Transcription Factors
  • Chromatin