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

## TL;DR

greenPipes is a new pipeline for analyzing CUT&RUN and greenCUT&RUN data, offering integrated tools for genome-localization studies.

## Contribution

greenPipes introduces a comprehensive, fine-tuned pipeline for CUT&RUN data analysis with integrated multi-omics capabilities.

## Key findings

- greenPipes provides optimized parameters for CUT&RUN and greenCUT&RUN data analysis.
- The pipeline supports data integration with other -omics technologies.
- Test datasets and annotations are publicly available for use.

## Abstract

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.

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/.

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

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