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greenPipes: an integrated data analysis pipeline for greenCUT&RUN and CUT&RUN genome-localization datasets
Sheikh Nizamuddin1,2, H T Marc Timmers1,2
1Department of Urology, Medical Center-University of Freiburg, Freiburg, 79016, Germany.
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.
