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MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens

Author(s)
Li, Wei; Xu, Han; Xiao, Tengfei; Cong, Le; Love, Michael I.; Zhang, Feng; Irizarry, Rafael A.; Liu, Jun S.; Brown, Myles; Liu, X. Shirley; ... Show more Show less
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Abstract
We propose the Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout (MAGeCK) method for prioritizing single-guide RNAs, genes and pathways in genome-scale CRISPR/Cas9 knockout screens. MAGeCK demonstrates better performance compared with existing methods, identifies both positively and negatively selected genes simultaneously, and reports robust results across different experimental conditions. Using public datasets, MAGeCK identified novel essential genes and pathways, including EGFR in vemurafenib-treated A375 cells harboring a BRAF mutation. MAGeCK also detected cell type-specific essential genes, including BCR and ABL1, in KBM7 cells bearing a BCR-ABL fusion, and IGF1R in HL-60 cells, which depends on the insulin signaling pathway for proliferation.
Date issued
2014-12
URI
http://hdl.handle.net/1721.1/92852
Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences; McGovern Institute for Brain Research at MIT
Journal
Genome Biology
Publisher
BioMed Central Ltd
Citation
Li, Wei, Han Xu, Tengfei Xiao, Le Cong, Michael I Love, Feng Zhang, Rafael A Irizarry, Jun S Liu, Myles Brown, and X Shirley Liu. “MAGeCK Enables Robust Identification of Essential Genes from Genome-Scale CRISPR/Cas9 Knockout Screens.” Genome Biology 15, no. 12 (December 2014).
Version: Final published version
ISSN
1465-6906
1474-7596

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