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Measuring error rates in genomic perturbation screens: gold standards for human functional genomics

Traver Hart, Kevin R. Brown, Fabrice Sircoulomb, Robert Rottapel, Jason Moffat
doi: https://doi.org/10.1101/003327
Traver Hart
1Donnelly Centre and Banting and Best Department of Medical Research, University of Toronto, Toronto, Canada
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Kevin R. Brown
1Donnelly Centre and Banting and Best Department of Medical Research, University of Toronto, Toronto, Canada
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Fabrice Sircoulomb
3Campbell Family Cancer Research Institute, Ontario Cancer Institute, Princess Margaret Hospital, University Health Network, Toronto, Canada
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Robert Rottapel
3Campbell Family Cancer Research Institute, Ontario Cancer Institute, Princess Margaret Hospital, University Health Network, Toronto, Canada
4Department of Medical Biophysics, University of Toronto, Toronto, Canada
5Division of Rheumatology, Department of Medicine, St. Michael’s Hospital, Toronto, Canada
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Jason Moffat
1Donnelly Centre and Banting and Best Department of Medical Research, University of Toronto, Toronto, Canada
2Department of Molecular Genetics, University of Toronto, Toronto, Canada
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Abstract

Technological advancement has opened the door to systematic genetics in mammalian cells. Genome-scale loss-of-function screens can assay fitness defects induced by partial gene knockdown, using RNA interference, or complete gene knockout, using new CRISPR techniques. These screens can reveal the basic blueprint required for cellular proliferation. Moreover, comparing healthy to cancerous tissue can uncover genes that are essential only in the tumor; these genes are targets for the development of specific anticancer therapies. Unfortunately, progress in this field has been hampered by offtarget effects of perturbation reagents and poorly quantified error rates in large-scale screens. To improve the quality of information derived from these screens, and to provide a framework for understanding the capabilities and limitations of CRISPR technology, we derive gold-standard reference sets of essential and nonessential genes, and provide a Bayesian classifier of gene essentiality that outperforms current methods on both RNAi and CRISPR screens. Our results indicate that CRISPR technology is more sensitive than RNAi, and that both techniques have nontrivial false discovery rates that can be mitigated by rigorous analytical methods.

Footnotes

  • Author email addresses:

    Traver Hart (traver.hart{at}gmail.com)

    Kevin Brown (kr.brown{at}utoronto.ca)

    Fabrice Sircoulomb (sircoulombf{at}gmail.com)

    Robert Rottapel (rottapel{at}gmail.com)

    Jason Moffat (j.moffat{at}utoronto.ca)

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-NC-ND 4.0 International license.
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Posted March 17, 2014.
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Measuring error rates in genomic perturbation screens: gold standards for human functional genomics
Traver Hart, Kevin R. Brown, Fabrice Sircoulomb, Robert Rottapel, Jason Moffat
bioRxiv 003327; doi: https://doi.org/10.1101/003327
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Measuring error rates in genomic perturbation screens: gold standards for human functional genomics
Traver Hart, Kevin R. Brown, Fabrice Sircoulomb, Robert Rottapel, Jason Moffat
bioRxiv 003327; doi: https://doi.org/10.1101/003327

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