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CUT&RUNTools 2.0: a pipeline for single-cell and bulk-level CUT&RUN and CUT&Tag data analysis
Fulong Yu1,2,3,4, Vijay G Sankaran1,2,3,4, Guo-Cheng Yuan1,2,3,5
1Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Motivation:
Genome-wide profiling of transcription factor binding and chromatin states is a widely-used approach for mechanistic understanding of gene regulation. Recent technology development has enabled such profiling at single-cell resolution. However, an end-to-end computational pipeline for analyzing such data is still lacking.
Results:
Here, we have developed a flexible pipeline for analysis and visualization of single-cell CUT&Tag and CUT&RUN data, which provides functions for sequence alignment, quality control, dimensionality reduction, cell clustering, data aggregation and visualization. Furthermore, it is also seamlessly integrated with the functions in original CUT&RUNTools for population-level analyses. As such, this provides a valuable toolbox for the community.
Availability And Implementation:
https://github.com/fl-yu/CUT-RUNTools-2.0.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
