Measuring error rates in genomic perturbation screens: gold standards for human functional genomics
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 revea...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Springer Nature
2014-07-01
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| Series: | Molecular Systems Biology |
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| Online Access: | https://doi.org/10.15252/msb.20145216 |
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| _version_ | 1849738805576204288 |
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| author | Traver Hart Kevin R Brown Fabrice Sircoulomb Robert Rottapel Jason Moffat |
| author_facet | Traver Hart Kevin R Brown Fabrice Sircoulomb Robert Rottapel Jason Moffat |
| author_sort | Traver Hart |
| collection | DOAJ |
| description | 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 off‐target 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. |
| format | Article |
| id | doaj-art-0cd985cd287f4bd3a734bca60d704b25 |
| institution | DOAJ |
| issn | 1744-4292 |
| language | English |
| publishDate | 2014-07-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj-art-0cd985cd287f4bd3a734bca60d704b252025-08-20T03:06:27ZengSpringer NatureMolecular Systems Biology1744-42922014-07-0110711610.15252/msb.20145216Measuring error rates in genomic perturbation screens: gold standards for human functional genomicsTraver Hart0Kevin R Brown1Fabrice Sircoulomb2Robert Rottapel3Jason Moffat4Donnelly Centre and Banting and Best Department of Medical Research, University of TorontoDonnelly Centre and Banting and Best Department of Medical Research, University of TorontoCampbell Family Cancer Research Institute, Ontario Cancer Institute, Princess Margaret Hospital, University Health NetworkCampbell Family Cancer Research Institute, Ontario Cancer Institute, Princess Margaret Hospital, University Health NetworkDonnelly Centre and Banting and Best Department of Medical Research, University of TorontoAbstract 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 off‐target 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.https://doi.org/10.15252/msb.20145216cancerCRISPRessential genesRNAishRNA |
| spellingShingle | Traver Hart Kevin R Brown Fabrice Sircoulomb Robert Rottapel Jason Moffat Measuring error rates in genomic perturbation screens: gold standards for human functional genomics Molecular Systems Biology cancer CRISPR essential genes RNAi shRNA |
| title | Measuring error rates in genomic perturbation screens: gold standards for human functional genomics |
| title_full | Measuring error rates in genomic perturbation screens: gold standards for human functional genomics |
| title_fullStr | Measuring error rates in genomic perturbation screens: gold standards for human functional genomics |
| title_full_unstemmed | Measuring error rates in genomic perturbation screens: gold standards for human functional genomics |
| title_short | Measuring error rates in genomic perturbation screens: gold standards for human functional genomics |
| title_sort | measuring error rates in genomic perturbation screens gold standards for human functional genomics |
| topic | cancer CRISPR essential genes RNAi shRNA |
| url | https://doi.org/10.15252/msb.20145216 |
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