MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens
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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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The distribution of sgRNAs between plasmids/AAVs and chow/WD livers were very similar, suggesting most sgRNAs did not change in frequency and indicating a lack of genetic drift.
“We compared sgRNA distributions from different screening steps and found the distribution between plasmids/AAVs (the starting points) and chow/WD livers (the endpoints) were very similar (Figure S2E and Table S3), suggesting that most of the sgRNAs in the screen did not change in frequency, which is also true for other CRISPR screens14, and indicated a lack of genetic drift.”
From Positive selection of somatically mutated clones identifies adaptive pathways in metabolic liver disease (2023) · cites this paper as [14]
In Materials and methods (The MAGeCK algorithm; page unavailable), the paper assumes that most sgRNAs have no effect on selection, but cautions that this may not hold in some scenarios. It does not establish that sgRNA frequencies remained stable in other CRISPR screens; the plasmid/AAV and liver comparison is the citing authors’ own finding, not a result attributed to this source. (LLM, conf=0.82)
Experimental — accuracy not yet measuredTo validate nominated hits, gene-level phenotype scores were also calculated using the MAGeCK pipeline based on sgRNA raw counts from both clones.
“To validate the nominated hits, gene-level phenotype scores were also calculated using the MAGeCK pipeline61 based on sgRNA raw counts from both clones, and results are provided in Source Data Fig. 2.”
From Genome-scale CRISPR screens identify PTGES3 as a direct modulator of androgen receptor function in advanced prostate cancer (2025) · cites this paper as [61]
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Self-citation
- Authors
- Li, W., Xu, H., Xiao, T., Cong, L., Love, M. I., Zhang, F., Irizarry, R. A., Liu, J. S., Brown, M., & Liu, X. S.
- Affiliations
- Harvard University (US)
- Dana-Farber Cancer Institute (US)
- Broad Institute (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Liu, X Shirley
- ORCID
- Venue
- Genome Biology
- Published
- 2014-12-05
- Volume
- 15
- Issue
- 12
- Pages
- 554-554
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC4290824
- OpenAlex
- W2100122648
- Cited by
- 2,684
- References
- 38
- Citations by year
- 2026: 329 · 2025: 449 · 2024: 415 · 2023: 351 · 2022: 299 · 2021: 276 · 2020: 226 · 2019: 165 · 2018: 90 · 2017: 41 · 2016: 25 · 2015: 11 · 2014: 2 · 2013: 1
- FWCI
- 10.79
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- National Institutes of Health (NIH-R01)
- National Cancer Institute (T32CA009337)
- National Institute of General Medical Sciences (R01GM099409)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- MAGeCK, CRISPR-Cas9 knockout screen, essential genes, gene prioritization, positive and negative selection, vemurafenib, EGFR, BRAF mutation, BCR-ABL, IGF-1 receptor, insulin signaling pathway
- MeSH terms
- Algorithms, Humans, Neoplasms, Gene Expression Regulation, Neoplastic, HL-60 Cells, Computational Biology, Genetic Predisposition to Disease, Genes, Essential, Cell Line, Tumor, Gene Knockout Techniques, CRISPR-Cas Systems, CRISPR-Associated Proteins
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