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Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects.
Dempster, Joshua M; Boyle, Isabella; Vazquez, Francisca; Root, David E; Boehm, Jesse S; Hahn, William C; Tsherniak, Aviad; McFarland, James M.
Afiliación
  • Dempster JM; Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
  • Boyle I; Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
  • Vazquez F; Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
  • Root DE; Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
  • Boehm JS; Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
  • Hahn WC; Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
  • Tsherniak A; Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA, 02215, USA.
  • McFarland JM; Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
Genome Biol ; 22(1): 343, 2021 12 20.
Article en En | MEDLINE | ID: mdl-34930405
CRISPR loss of function screens are powerful tools to interrogate biology but exhibit a number of biases and artifacts that can confound the results. Here, we introduce Chronos, an algorithm for inferring gene knockout fitness effects based on an explicit model of cell proliferation dynamics after CRISPR gene knockout. We test Chronos on two pan-cancer CRISPR datasets and one longitudinal CRISPR screen. Chronos generally outperforms competitors in separation of controls and strength of biomarker associations, particularly when longitudinal data is available. Additionally, Chronos exhibits the lowest copy number and screen quality bias of evaluated methods. Chronos is available at https://github.com/broadinstitute/chronos .
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Dinámica Poblacional / Genoma / Biología Computacional / Sistemas CRISPR-Cas Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Dinámica Poblacional / Genoma / Biología Computacional / Sistemas CRISPR-Cas Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos