title: BAGEL: a computational framework for identifying essential genes from pooled library screens.
abstract: BACKGROUND
  The adaptation of the CRISPR-Cas9 system to pooled library gene knockout screens in mammalian cells represents a major technological leap over RNA interference, the prior state of the art. New methods for analyzing the data and evaluating results are needed.
  
  
  RESULTS
  We offer BAGEL (Bayesian Analysis of Gene EssentiaLity), a supervised learning method for analyzing gene knockout screens. Coupled with gold-standard reference sets of essential and nonessential genes, BAGEL offers significantly greater sensitivity than current methods, while computational optimizations reduce runtime by an order of magnitude.
  
  
  CONCLUSIONS
  Using BAGEL, we identify ~2000 fitness genes in pooled library knockout screens in human cell lines at 5 % FDR, a major advance over competing platforms. BAGEL shows high sensitivity and specificity even across screens performed by different labs using different libraries and reagents.
authors.affiliation: Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. traver.hart@gmail.com.
authors.forename: Traver
authors.initials: T
authors.lastname: Hart
authors.affiliation: Donnelly Centre, University of Toronto, Toronto, Canada.|Department of Molecular Genetics, University of Toronto, Toronto, Canada.
authors.forename: Jason
authors.initials: J
authors.lastname: Moffat
mesh_terms: D045744:Cell Line, Tumor; D019295:Computational Biology / Q000379:methods*; D004847:Epithelial Cells / Q000378:metabolism; D055786:Gene Knockout Techniques; D015723:Gene Library; D020043:Genes, Essential; D056084:Genetic Fitness; D005909:Glioblastoma / Q000235:genetics; D045325:HCT116 Cells; D006367:HeLa Cells; D006801:Humans; D000069550:Machine Learning; D008957:Models, Genetic; D034622:RNA Interference; D012680:Sensitivity and Specificity
keywords: CRISPR; Cancer; Essential genes; Functional genomics; Genetic screens