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CRISPR-SURF: Discovering regulatory elements by deconvolution of CRISPR tiling screen data
Jonathan Y Hsu,
Charles P Fulco,
Mitchel A Cole,
Matthew C. Canver,
James A Guo,
Stuart H Orkin,
Jesse M Engreitz,
Eric S Lander,
J. Keith Joung,
Daniel E. Bauer,
Posted 13 Jun 2018
bioRxiv DOI: 10.1101/345850 (published DOI: 10.1038/s41592-018-0225-6)
Posted 13 Jun 2018
Tiling screens using CRISPR-Cas technologies provide a powerful approach to map regulatory elements to phenotypes of interest, but computational methods that effectively model these experimental approaches for different CRISPR technologies are not readily available. Here we present CRISPR-SURF, a deconvolution framework to identify functional regulatory regions in the genome from data generated by CRISPR-Cas nuclease, CRISPR interference (CRISPRi), or CRISPR activation (CRISPRa) tiling screens. We validated CRISPR-SURF on previously published and new data, identifying both experimentally validated and new potential regulatory elements. With CRISPR tiling screens now being increasingly used to elucidate the regulatory architecture of the non-coding genome, CRISPR-SURF provides a generalizable and accessible solution for the discovery of regulatory elements.
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