The paper introduces MAGeCK, a statistical method for identifying essential genes, sgRNAs, and pathways from genome-scale CRISPR/Cas9 knockout screens. MAGeCK outperforms existing methods in terms of false discovery rate control and sensitivity, and can handle different sequencing depths and numbers of sgRNAs per gene. The method was evaluated using public datasets, demonstrating its ability to identify novel essential genes and pathways, including *EGFR* in vemurafenib-treated A375 cells with a *BRAF* mutation, *BCR* and *ABL1* in KBM7 cells with a *BCR-ABL* fusion, and *IGF1R* in HL-60 cells. MAGeCK also enables bi-directional and cell type-specific screening, providing insights into drug response and potential combination therapies. The algorithm's robustness and effectiveness make it a valuable tool for analyzing CRISPR/Cas9 knockout screens.The paper introduces MAGeCK, a statistical method for identifying essential genes, sgRNAs, and pathways from genome-scale CRISPR/Cas9 knockout screens. MAGeCK outperforms existing methods in terms of false discovery rate control and sensitivity, and can handle different sequencing depths and numbers of sgRNAs per gene. The method was evaluated using public datasets, demonstrating its ability to identify novel essential genes and pathways, including *EGFR* in vemurafenib-treated A375 cells with a *BRAF* mutation, *BCR* and *ABL1* in KBM7 cells with a *BCR-ABL* fusion, and *IGF1R* in HL-60 cells. MAGeCK also enables bi-directional and cell type-specific screening, providing insights into drug response and potential combination therapies. The algorithm's robustness and effectiveness make it a valuable tool for analyzing CRISPR/Cas9 knockout screens.