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CRISPR-Decryptr reveals cis-regulatory elements from noncoding perturbation screens

View ORCID ProfileAnders Rasmussen, Tarmo Äijö, View ORCID ProfileMariano Ignacio Gabitto, Nicholas Carriero, View ORCID ProfileNeville Sanjana, View ORCID ProfileJane Skok, View ORCID ProfileRichard Bonneau
doi: https://doi.org/10.1101/2020.08.13.247007
Anders Rasmussen
1Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
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  • ORCID record for Anders Rasmussen
Tarmo Äijö
1Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
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Mariano Ignacio Gabitto
1Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
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Nicholas Carriero
3Scientific Computing Core, Flatiron Institute, Simons Foundation, New York, NY, 10010, USA
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Neville Sanjana
4New York Genome Center, New York, NY, 10013, USA
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Jane Skok
5New York University, Department of Biology, New York, NY 10012, USA
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Richard Bonneau
1Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
2New York University, Center for Data Science, New York, NY 10010, USA
5New York University, Department of Biology, New York, NY 10012, USA
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  • For correspondence: arasmussen@flatironinstitute.org
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Abstract

Clustered Regularly Interspace Short Palindromic Repeats (CRISPR)-Cas9 genome editing methods provide the tools necessary to examine phenotypic impacts of targeted perturbations in high-throughput screens. While these technologies have the potential to reveal functional elements with direct therapeutic applications, statistical techniques to analyze noncoding screen data remain limited. We present CRISPR-Decryptr, a computational tool for the analysis of CRISPR noncoding screens. Our method leverages experimental design: accounting for multiple conditions, controls, and replicates to infer the regulatory landscape of noncoding genomic regions. We validate our method on a variety of mutagenesis, CRISPR activation, and CRISPR interference screens, extracting new insights from previously published data.

Competing Interest Statement

A.R. owns stock in Editas medicine and 10x Genomics. T.A. owns stock in 10x Genomics. R.B. has ongoing or recent consulting or advisory relationships with Eli Lily, Merus, Merck and Epistemic AI.

Footnotes

  • https://github.com/anders-w-rasmussen/crispr_decryptr

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted August 14, 2020.
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CRISPR-Decryptr reveals cis-regulatory elements from noncoding perturbation screens
Anders Rasmussen, Tarmo Äijö, Mariano Ignacio Gabitto, Nicholas Carriero, Neville Sanjana, Jane Skok, Richard Bonneau
bioRxiv 2020.08.13.247007; doi: https://doi.org/10.1101/2020.08.13.247007
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CRISPR-Decryptr reveals cis-regulatory elements from noncoding perturbation screens
Anders Rasmussen, Tarmo Äijö, Mariano Ignacio Gabitto, Nicholas Carriero, Neville Sanjana, Jane Skok, Richard Bonneau
bioRxiv 2020.08.13.247007; doi: https://doi.org/10.1101/2020.08.13.247007

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