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Keywords {🔍}

genes, sgrnas, mageck, pubmed, crisprcas, gene, knockout, article, selected, read, google, scholar, cas, file, additional, screens, dataset, screening, sgrna, figure, essential, variance, sequencing, melanoma, leukemia, cells, cell, counts, central, methods, negatively, riger, rsa, model, samples, pathways, ranked, datasets, identified, identify, edger, robust, positively, screen, deseq, analysis, number, experiments, distribution, targeting,

Topics {✒️}

genome-wide crispr/cas9 knockout 𝑁 𝐵 𝑥 genome-scale crispr/cas9 knockout 𝜇 𝑖 𝐴 crispr/cas9 knockout screening crispr/cas9 knockout screen crispr/cas9 knockout screens cell-type-specific screening genome-scale rnai screens genome-scale shrna screens crispr/cas9 knockout system false discovery rate large-scale rnai screens rna-guided cas9 nucleases crispr-cas nucleases mitogen-activated protein kinase 𝑥 ^ 𝑖 crispr/cas systems induce double-strand breaks prioritizing single-guide rnas dana-farber cancer institute target mutagenesis induced org/cancer/software/rnai/riger/] dual-receptor inhibitor bms-536924 negative binomial p-values article download pdf high-throughput sequencing experiments genome editing toolbox rna-seq read counts high-throughput profiling zinc finger protein high-throughput sequencing data crispr/cas9 library high-throughput sequencing counts perform bi-directional analysis crispr-cas9 system cost-effective manner [3]-[6] short hairpin rna full size image tumor suppressor kinase highly parallel identification cell type differences differential expression analysis open source software multiplex genome engineering original screen design identifying differential expression high-throughput screening 7-day plx-treated samples double-strand breaks

Schema {🗺️}

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         headline:MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens
         description: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.
         datePublished:2014-12-05T00:00:00Z
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            Essential Gene
            Read Count
            Sequencing Depth
            Negative Binomial Distribution
            Animal Genetics and Genomics
            Human Genetics
            Plant Genetics and Genomics
            Microbial Genetics and Genomics
            Bioinformatics
            Evolutionary Biology
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      headline:MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens
      description: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.
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         Sequencing Depth
         Negative Binomial Distribution
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         Plant Genetics and Genomics
         Microbial Genetics and Genomics
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      name:X Shirley Liu
      affiliation:
            name:Dana-Farber Cancer Institute, Harvard School of Public Health
            address:
               name:Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
               type:PostalAddress
            type:Organization
            name:Dana-Farber Cancer Institute
            address:
               name:Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, USA
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
      name:Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, USA
      name:Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
      name:Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, USA
      name:Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, USA
      name:Division of Molecular and Cellular Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA
      name:Broad Institute of MIT and Harvard, Cambridge, USA
      name:McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA
      name:Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
      name:Broad Institute of MIT and Harvard, Cambridge, USA
      name:McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA
      name:Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
      name:Department of Statistics, Harvard University, Cambridge, USA
      name:Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, USA
      name:Division of Molecular and Cellular Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA
      name:Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, USA
      name:Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
      name:Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, USA

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