The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Measuring error rates in genomic perturbation screens: gold standards for human functional genomics
Open accessPublished version of a preprint
Abstract
Technological advancement has opened the door to systematic genetics in mammalian cells. Genome‐scale loss‐of‐function screens can assay fitness defects induced by partial gene knockdown, using RNA interference, or complete gene knockout, using new CRISPR techniques. These screens can reveal the basic blueprint required for cellular proliferation. Moreover, comparing healthy to cancerous tissue can uncover genes that are essential only in the tumor; these genes are targets for the development of specific anticancer therapies. Unfortunately, progress in this field has been hampered by off‐target effects of perturbation reagents and poorly quantified error rates in large‐scale screens. To improve the quality of information derived from these screens, and to provide a framework for understanding the capabilities and limitations of CRISPR technology, we derive gold‐standard reference sets of essential and nonessential genes, and provide a Bayesian classifier of gene essentiality that outperforms current methods on both RNAi and CRISPR screens. Our results indicate that CRISPR technology is more sensitive than RNAi and that both techniques have nontrivial false discovery rates that can be mitigated by rigorous analytical methods.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The reproducibility of essentiality phenotypes in replicate screens confirmed consistent reagent behavior and identified several known core essential genes.
“the reproducibility of essentiality phenotypes in replicate screens confirmed consistent reagent behavior and identified several known “core essential” genes”
From A Landscape of Therapeutic Cooperativity in KRAS Mutant Cancers Reveals Principles for Controlling Tumor Evolution (2017) · cites this paper as Hart et al., 2014
The Results section on core essentials (page unavailable) says that repeated essentiality calls across high-performing cell-line screens helped identify 291 likely core essential genes. The paper does not describe these as replicate screens or say that the observations confirmed consistent reagent behavior; its Introduction mentions consistency of hairpin phenotypes as an approach used in other studies. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Multiplex Genome Engineering Using CRISPR/Cas Systems
Cong, L., Ran, F. A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P. D., Wu, X., Jiang, W., Marraffini, L. A., et al. (2013) · Science · doi:10.1126/science.1231143 · Cited by 15,339
RNA-Guided Human Genome Engineering via Cas9
Mali, P., Yang, L., Esvelt, K. M., Aach, J., Guell, M., DiCarlo, J. E., Norville, J. E., & Church, G. M. (2013) · Science · doi:10.1126/science.1232033 · Cited by 9,210
Genome-scale CRISPR-Cas9 knockout screening in human cells
Shalem, O., Sanjana, N. E., Hartenian, E., Shi, X., Scott, D. A., Mikkelsen, T. S., Heckl, D., Ebert, B. L., Root, D. E., Doench, J. G., et al. (2014) · Science · doi:10.1126/science.1247005 · Cited by 5,234
Evolution and functional impact of rare coding variation from deep sequencing of human exomes
Tennessen, J. A., Bigham, A. W., O’Connor, T. D., Fu, W., Kenny, E. E., Gravel, S., McGee, S., Do, R., Liu, X., Jun, G., et al. (2012) · Science · doi:10.1126/science.1219240 · Cited by 1,613
Role of duplicate genes in genetic robustness against null mutations
Gu, Z., Steinmetz, L. M., Gu, X., Scharfe, C., Davis, R. W., & Li, W.-H. (2003) · Nature · doi:10.1038/nature01198 · Cited by 889
RNA sequencing reveals two major classes of gene expression levels in metazoan cells
Hebenstreit, D., Fang, M., Gu, M., Charoensawan, V., van Oudenaarden, A., & Teichmann, S. A. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.28 · Cited by 289
Flagged first, then by citations
Research works printed but not linked: 46
- Babij C, Zhang Y, Kurzeja RJ, Munzli A, Shehabeldin A, Fernando M, Quon K, Kassner PD, Ruefli‐Brasse AA, Watson VJ, Fajardo F, Jackson A, Zondlo J, Sun Y, Ellison AR, Plewa CA, San MT, Robinson J, McCarter J, Schwandner R et al (2011) STK33 kinase activity is nonessential in KRAS‐dependent cancer cells. Cancer Res 71: 5818–5826 · DOI
- Boutros M, Kiger AA, Armknecht S, Kerr K, Hild M, Koch B, Haas SA, Paro R, Perrimon N, Heidelberg Fly Array C (2004) Genome‐wide RNAi analysis of growth and viability in Drosophila cells. Science 303: 832–835 · DOI
- Burckstummer T, Banning C, Hainzl P, Schobesberger R, Kerzendorfer C, Pauler FM, Chen D, Them N, Schischlik F, Rebsamen M, Smida M, de laCruz FF, Lapao A, Liszt M, Eizinger B, Guenzl PM, Blomen VA, Konopka T, Gapp B, Parapatics K et al (2013) A reversible gene trap collection empowers haploid genetics in human cells. Nat Methods 10: 1548–7105. · DOI
- Carette JE, Guimaraes CP, Varadarajan M, Park AS, Wuethrich I, Godarova A, Kotecki M, Cochran BH, Spooner E, Ploegh HL, Brummelkamp TR (2009) Haploid genetic screens in human cells identify host factors used by pathogens. Science 326: 1231–1235 · DOI
- Castle WE, Little CC (1910) On a modified mendelian ratio among yellow mice. Science 32: 868–870 · DOI
- Chavali S, Barrenas F, Kanduri K, Benson M (2010) Network properties of human disease genes with pleiotropic effects. BMC Syst Biol 4: 78 · DOI
- Cheung HW, Cowley GS, Weir BA, Boehm JS, Rusin S, Scott JA, East A, Ali LD, Lizotte PH, Wong TC, Jiang G, Hsiao J, Mermel CH, Getz G, Barretina J, Gopal S, Tamayo P, Gould J, Tsherniak A, Stransky N et al (2011) Systematic investigation of genetic vulnerabilities across cancer cell lines reveals lineage‐specific dependencies in ovarian cancer. Proc Natl Acad Sci USA 108: 12372–12377 · DOI · Paper page
- Cuenot L (1905) Les races pures et leurs combinaisons chez les souris. Archives de Zoologie Experimentale et Generale 4: 123–132
- Davoli T, Xu AW, Mengwasser KE, Sack LM, Yoon JC, Park PJ, Elledge SJ (2013) Cumulative haploinsufficiency and triplosensitivity drive aneuploidy patterns and shape the cancer genome. Cell 155: 948–962 · DOI · Paper page
- Dickerson JE, Zhu A, Robertson DL, Hentges KE (2011) Defining the role of essential genes in human disease. PLoS ONE 6: e27368 · DOI
- Dietzl G, Chen D, Schnorrer F, Su KC, Barinova Y, Fellner M, Gasser B, Kinsey K, Oppel S, Scheiblauer S, Couto A, Marra V, Keleman K, Dickson BJ (2007) A genome‐wide transgenic RNAi library for conditional gene inactivation in Drosophila. Nature 448: 151–156 · DOI · Paper page
- Echeverri CJ, Beachy PA, Baum B, Boutros M, Buchholz F, Chanda SK, Downward J, Ellenberg J, Fraser AG, Hacohen N, Hahn WC, Jackson AL, Kiger A, Linsley PS, Lum L, Ma Y, Mathey‐Prevot B, Root DE, Sabatini DM, Taipale J et al (2006) Minimizing the risk of reporting false positives in large‐scale RNAi screens. Nat Methods 3: 777–779 · DOI
- Giaever G, Chu AM, Ni L, Connelly C, Riles L, Veronneau S, Dow S, Lucau‐Danila A, Anderson K, Andre B, Arkin AP, Astromoff A, El‐Bakkoury M, Bangham R, Benito R, Brachat S, Campanaro S, Curtiss M, Davis K, Deutschbauer A et al (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature 418: 387–391 · DOI · Paper page
- Hart GT, Ramani AK, Marcotte EM (2006) How complete are current yeast and human protein‐interaction networks? Genome Biol 7: 120 · DOI
- Hart GT, Lee I, Marcotte ER (2007) A high‐accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality. BMC Bioinformatics 8: 236 · DOI
- Hart T, Komori HK, Lamere S, Podshivalova K, Salomon DR (2013) Finding the active genes in deep RNA‐seq gene expression studies. BMC Genomics 14: 778 · DOI
- Havugimana PC, Hart GT, Nepusz T, Yang H, Turinsky AL, Li Z, Wang PI, Boutz DR, Fong V, Phanse S, Babu M, Craig SA, Hu P, Wan C, Vlasblom J, Dar VU, Bezginov A, Clark GW, Wu GC, Wodak SJ et al (2012) A census of human soluble protein complexes. Cell 150: 1068–1081 · DOI
- Jansen R, Gerstein M (2004) Analyzing protein function on a genomic scale: the importance of gold‐standard positives and negatives for network prediction. Curr Opin Microbiol 7: 535–545 · DOI
- Jeong H, Mason SP, Barabasi AL, Oltvai ZN (2001) Lethality and centrality in protein networks. Nature 411: 41–42 · DOI
- Kaelin WG Jr (2012) Molecular biology. Use and abuse of RNAi to study mammalian gene function. Science 337: 421–422 · DOI
- Kamath RS, Fraser AG, Dong Y, Poulin G, Durbin R, Gotta M, Kanapin A, Le Bot N, Moreno S, Sohrmann M, Welchman DP, Zipperlen P, Ahringer J (2003) Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature 421: 231–237 · DOI
- Kim DU, Hayles J, Kim D, Wood V, Park HO, Won M, Yoo HS, Duhig T, Nam M, Palmer G, Han S, Jeffery L, Baek ST, Lee H, Shim YS, Lee M, Kim L, Heo KS, Noh EJ, Lee AR et al (2010) Analysis of a genome‐wide set of gene deletions in the fission yeast Schizosaccharomyces pombe. Nat Biotechnol 28: 617–623 · DOI · Paper page
- Liao BY, Zhang J (2008) Null mutations in human and mouse orthologs frequently result in different phenotypes. Proc Natl Acad Sci USA 105: 6987–6992 · DOI · Paper page
- Lohmueller KE, Indap AR, Schmidt S, Boyko AR, Hernandez RD, Hubisz MJ, Sninsky JJ, White TJ, Sunyaev SR, Nielsen R, Clark AG, Bustamante CD (2008) Proportionally more deleterious genetic variation in European than in African populations. Nature 451: 994–997 · DOI
- Luo B, Cheung HW, Subramanian A, Sharifnia T, Okamoto M, Yang X, Hinkle G, Boehm JS, Beroukhim R, Weir BA, Mermel C, Barbie DA, Awad T, Zhou X, Nguyen T, Piqani B, Li C, Golub TR, Meyerson M, Hacohen N et al (2008) Highly parallel identification of essential genes in cancer cells. Proc Natl Acad Sci USA 105: 20380–20385 · DOI
- Luo T, Masson K, Jaffe JD, Silkworth W, Ross NT, Scherer CA, Scholl C, Frohling S, Carr SA, Stern AM, Schreiber SL, Golub TR (2012) STK33 kinase inhibitor BRD‐8899 has no effect on KRAS‐dependent cancer cell viability. Proc Natl Acad Sci USA 109: 2860–2865 · DOI
- Makino T, Hokamp K, McLysaght A (2009) The complex relationship of gene duplication and essentiality. Trends Genet 25: 152–155 · DOI
- Marcotte R, Brown KR, Suarez F, Sayad A, Karamboulas K, Krzyzanowski PM, Sircoulomb F, Medrano M, Fedyshyn Y, Koh JL, van Dyk D, Fedyshyn B, Luhova M, Brito GC, Vizeacoumar FJ, Vizeacoumar FS, Datti A, Kasimer D, Buzina A, Mero P et al (2012) Essential gene profiles in breast, pancreatic, and ovarian cancer cells. Cancer Discov 2: 172–189 · DOI
- Moffat J, Reiling JH, Sabatini DM (2007) Off‐target effects associated with long dsRNAs in Drosophila RNAi screens. Trends Pharmacol Sci 28: 149–151 · DOI
- Nijhawan D, Zack TI, Ren Y, Strickland MR, Lamothe R, Schumacher SE, Tsherniak A, Besche HC, Rosenbluh J, Shehata S, Cowley GS, Weir BA, Goldberg AL, Mesirov JP, Root DE, Bhatia SN, Beroukhim R, Hahn WC (2012) Cancer vulnerabilities unveiled by genomic loss. Cell 150: 842–854 · DOI
- Paigen K (2003) One hundred years of mouse genetics: an intellectual history. I. The classical period (1902–1980). Genetics 163: 1–7 · DOI
- Popova T, Manie E, Stoppa‐Lyonnet D, Rigaill G, Barillot E, Stern MH (2009) Genome Alteration Print (GAP): a tool to visualize and mine complex cancer genomic profiles obtained by SNP arrays. Genome Biol 10: R128 · DOI
- Schlabach MR, Luo J, Solimini NL, Hu G, Xu Q, Li MZ, Zhao Z, Smogorzewska A, Sowa ME, Ang XL, Westbrook TF, Liang AC, Chang K, Hackett JA, Harper JW, Hannon GJ, Elledge SJ (2008) Cancer proliferation gene discovery through functional genomics. Science 319: 620–624 · DOI
- Scholl C, Frohling S, Dunn IF, Schinzel AC, Barbie DA, Kim SY, Silver SJ, Tamayo P, Wadlow RC, Ramaswamy S, Dohner K, Bullinger L, Sandy P, Boehm JS, Root DE, Jacks T, Hahn WC, Gilliland DG (2009) Synthetic lethal interaction between oncogenic KRAS dependency and STK33 suppression in human cancer cells. Cell 137: 821–834 · DOI
- Shao DD, Tsherniak A, Gopal S, Weir BA, Tamayo P, Stransky N, Schumacher SE, Zack TI, Beroukhim R, Garraway LA, Margolin AA, Root DE, Hahn WC, Mesirov JP (2012) ATARiS: computational quantification of gene suppression phenotypes from multi‐sample RNAi screens. Genome Res 23: 665–678. · DOI
- Shao DD, Tsherniak A, Gopal S, Weir BA, Tamayo P, Stransky N, Schumacher SE, Zack TI, Beroukhim R, Garraway LA, Margolin AA, Root DE, Hahn WC, Mesirov JP (2013) ATARiS: computational quantification of gene suppression phenotypes from multisample RNAi screens. Genome Res 23: 665–678 · DOI
- Silva JM, Marran K, Parker JS, Silva J, Golding M, Schlabach MR, Elledge SJ, Hannon GJ, Chang K (2008) Profiling essential genes in human mammary cells by multiplex RNAi screening. Science 319: 617–620 · DOI
- Solimini NL, Liang AC, Xu C, Pavlova NN, Xu Q, Davoli T, Li MZ, Wong KK, Elledge SJ (2013) STOP gene Phactr4 is a tumor suppressor. Proc Natl Acad Sci USA 110: E407–E414 · DOI
- Tilgner H, Knowles DG, Johnson R, Davis CA, Chakrabortty S, Djebali S, Curado J, Snyder M, Gingeras TR, Guigo R (2012) Deep sequencing of subcellular RNA fractions shows splicing to be predominantly co‐transcriptional in the human genome but inefficient for lncRNAs. Genome Res 22: 1616–1625 · DOI
- Tu Z, Wang L, Xu M, Zhou X, Chen T, Sun F (2006) Further understanding human disease genes by comparing with housekeeping genes and other genes. BMC Genomics 7: 31 · DOI
- Vizeacoumar FJ, Arnold R, Vizeacoumar FS, Chandrashekhar M, Buzina A, Young JT, Kwan JH, Sayad A, Mero P, Lawo S, Tanaka H, Brown KR, Baryshnikova A, Mak AB, Fedyshyn Y, Wang Y, Brito GC, Kasimer D, Makhnevych T, Ketela T et al (2013) A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities. Mol Syst Biol 9: 696 · DOI
- Wang T, Wei JJ, Sabatini DM, Lander ES (2013) Genetic Screens in Human Cells Using the CRISPR/Cas9 System. Science 343: 80–84. · DOI · Paper page
- Weiwer M, Spoonamore J, Wei J, Guichard B, Ross NT, Masson K, Silkworth W, Dandapani S, Palmer M, Scherer CA, Stern AM, Schreiber SL, Munoz B (2012) A Potent and Selective Quinoxalinone‐Based STK33 Inhibitor Does Not Show Synthetic Lethality in KRAS‐Dependent Cells. ACS Med Chem Lett 3: 1034–1038 · DOI
- White JK, Gerdin AK, Karp NA, Ryder E, Buljan M, Bussell JN, Salisbury J, Clare S, Ingham NJ, Podrini C, Houghton R, Estabel J, Bottomley JR, Melvin DG, Sunter D, Adams NC, Sanger Institute Mouse Genetics P, Tannahill D, Logan DW, Macarthur DG et al (2013) Genome‐wide generation and systematic phenotyping of knockout mice reveals new roles for many genes. Cell 154: 452–464. · DOI · Paper page
- Winzeler EA, Shoemaker DD, Astromoff A, Liang H, Anderson K, Andre B, Bangham R, Benito R, Boeke JD, Bussey H, Chu AM, Connelly C, Davis K, Dietrich F, Dow SW, El Bakkoury M, Foury F, Friend SH, Gentalen E, Giaever G et al (1999) Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 285: 901–906 · DOI · Paper page
- Zotenko E, Mestre J, O'Leary DP, Przytycka TM (2008) Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality. PLoS Comput Biol 4: e1000140 · DOI
Cited by
Sorted by citations
Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9
Doench, J. G., Fusi, N., Sullender, M., Hegde, M., Vaimberg, E. W., Donovan, K. F., Smith, I., Tothova, Z., Wilen, C., Orchard, R., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3437 · Cited by 4,637
Meyers, R. M., Bryan, J. G., McFarland, J. M., Weir, B. A., Sizemore, A. E., Xu, H., Dharia, N. V., Montgomery, P. G., Cowley, G. S., Pantel, S., et al. (2017) · Nature Genetics · doi:10.1038/ng.3984 · Cited by 1,952
Identification and characterization of essential genes in the human genome
Wang, T., Birsoy, K., Hughes, N. W., Krupczak, K. M., Post, Y., Wei, J. J., Lander, E. S., & Sabatini, D. M. (2015) · Science · doi:10.1126/science.aac7041 · Cited by 1,617
Genetic and functional drivers of diffuse large B cell lymphoma
Reddy, A., Zhang, J., Davis, N. S., Moffitt, A. B., Love, C. L., Waldrop, A., Leppa, S., Pasanen, A., Meriranta, L., Karjalainen-Lindsberg, M.-L., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.027 · Cited by 1,104
Horlbeck, M. A., Gilbert, L. A., Villalta, J. E., Adamson, B., Pak, R. A., Chen, Y., Fields, A. P., Park, C. Y., Corn, J. E., Kampmann, M., et al. (2016) · eLife · doi:10.7554/elife.19760 · Cited by 894
Chang, M. T., Asthana, S., Gao, S. P., Lee, B. H., Chapman, J. S., Kandoth, C., Gao, J., Socci, N. D., Solit, D. B., Olshen, A. B., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3391 · Cited by 808
Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing
Nuñez, J. K., Chen, J., Pommier, G. C., Cogan, J. Z., Replogle, J. M., Adriaens, C., Ramadoss, G. N., Shi, Q., Hung, K. L., Samelson, A. J., et al. (2021) · Cell · doi:10.1016/j.cell.2021.03.025 · Cited by 760
Evaluation and Design of Genome-Wide CRISPR/SpCas9 Knockout Screens
Hart, T., Tong, A. H. Y., Chan, K., Van Leeuwen, J., Seetharaman, A., Aregger, M., Chandrashekhar, M., Hustedt, N., Seth, S., Noonan, A., et al. (2017) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.117.041277 · Cited by 599
Self-citationFunctional genomic landscape of cancer-intrinsic evasion of killing by T cells
Lawson, K. A., Sousa, C. M., Zhang, X., Kim, E., Akthar, R., Caumanns, J. J., Yao, Y., Mikolajewicz, N., Ross, C., Brown, K. R., et al. (2020) · Nature · doi:10.1038/s41586-020-2746-2 · Cited by 443
Self-citationA Genome-wide CRISPR Screen in Primary Immune Cells to Dissect Regulatory Networks
Parnas, O., Jovanovic, M., Eisenhaure, T. M., Herbst, R. H., Dixit, A., Ye, C. J., Przybylski, D., Platt, R. J., Tirosh, I., Sanjana, N. E., et al. (2015) · Cell · doi:10.1016/j.cell.2015.06.059 · Cited by 440
Massively parallel assessment of human variants with base editor screens
Hanna, R. E., Hegde, M., Fagre, C. R., DeWeirdt, P. C., Sangree, A. K., Szegletes, Z., Griffith, A., Feeley, M. N., Sanson, K. R., Baidi, Y., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.012 · Cited by 316
Multilayered VBC score predicts sgRNAs that efficiently generate loss-of-function alleles
Michlits, G., Jude, J., Hinterndorfer, M., de Almeida, M., Vainorius, G., Hubmann, M., Neumann, T., Schleiffer, A., Burkard, T. R., Fellner, M., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0850-8 · Cited by 154
A quantitative framework for characterizing the evolutionary history of mammalian gene expression
Chen, J., Swofford, R., Johnson, J., Cummings, B. B., Rogel, N., Lindblad-Toh, K., Haerty, W., Palma, F. D., & Regev, A. (2019) · Genome Research · doi:10.1101/gr.237636.118 · Cited by 128
Lin, J., Zhang, Z., Zhang, S., Chen, J., & Wong, K. (2020) · Advanced Science · doi:10.1002/advs.201903562 · Cited by 101
Paralog buffering contributes to the variable essentiality of genes in cancer cell lines
De Kegel, B., & Ryan, C. J. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008466 · Cited by 92
Anderson, G. R., Winter, P. S., Lin, K. H., Nussbaum, D. P., Cakir, M., Stein, E. M., Soderquist, R. S., Crawford, L., Leeds, J. C., Newcomb, R., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.07.006 · Cited by 80
Massively parallel assessment of human variants with base editor screens
Hanna, R. E., Hegde, M., Fagre, C. R., DeWeirdt, P. C., Sangree, A. K., Szegletes, Z., Griffith, A., Feeley, M. N., Sanson, K. R., Baidi, Y., et al. (2020) · doi:10.1101/2020.05.17.100818 · Cited by 314
Intrinsic targeting of host RNA by Cas13 constrains its utility
Li, Z., Li, Z., Cheng, X., Wang, S., Wang, X., Ma, S., Lu, Z., Zhang, H., Zhao, W., Chen, Z., et al. (2023) · Nature Biomedical Engineering · doi:10.1038/s41551-023-01109-y · Cited by 31
Goh, C. J. H., Wong, J. H., El Farran, C., Tan, B. X., Coffill, C. R., Loh, Y.-H., Lane, D., & Arumugam, P. (2021) · G3 Genes|Genomes|Genetics · doi:10.1093/g3journal/jkaa069 · Cited by 20
Metadata
- Authors
- Hart, T., Brown, K. R., Sircoulomb, F., Rottapel, R., & Moffat, J.
- Affiliations
- University of Toronto (CA)
- University Health Network (CA)
- St. Michael's Hospital (CA)
- Venue
- Molecular Systems Biology
- Published
- 2014-07-01
- Volume
- 10
- Issue
- 7
- Pages
- 733-733
- ISSN
- 1744-4292 (ISSN-L)
- PMC
- PMC4299491
- OpenAlex
- W2138164217
- Cited by
- 398
- References
- 6
- Citations by year
- 2026: 18 · 2025: 37 · 2024: 32 · 2023: 33 · 2022: 30 · 2021: 57 · 2020: 47 · 2019: 35 · 2018: 32 · 2017: 43 · 2016: 19 · 2015: 14 · 2014: 1
- FWCI
- 8.48
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Molecular Systems Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Ontario Ministry of Research and Innovation's GL2 Program
- Selective Therapies Program at the Ontario Institute for Cancer Research
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Keywords
- error rate, gene essentiality, CRISPR, RNA interference, loss-of-function screen, off-target effects, false discovery rate, Bayesian classifier, cancer genes, anticancer drug targets
- MeSH terms
- Bayes Theorem, Humans, Models, Theoretical, Neoplasms, Reference Standards, Sensitivity and Specificity, Software, Genome, Human, Computational Biology, Genes, Essential, Genomics, RNA Interference, Cell Line, Tumor, Genetic Fitness, Clustered Regularly Interspaced Short Palindromic Repeats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
