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Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects
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 C...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8686573/ https://www.ncbi.nlm.nih.gov/pubmed/34930405 http://dx.doi.org/10.1186/s13059-021-02540-7 |
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author | Dempster, Joshua M. Boyle, Isabella Vazquez, Francisca Root, David E. Boehm, Jesse S. Hahn, William C. Tsherniak, Aviad McFarland, James M. |
author_facet | Dempster, Joshua M. Boyle, Isabella Vazquez, Francisca Root, David E. Boehm, Jesse S. Hahn, William C. Tsherniak, Aviad McFarland, James M. |
author_sort | Dempster, Joshua M. |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02540-7. |
format | Online Article Text |
id | pubmed-8686573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86865732021-12-20 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. Genome Biol Method 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02540-7. BioMed Central 2021-12-20 /pmc/articles/PMC8686573/ /pubmed/34930405 http://dx.doi.org/10.1186/s13059-021-02540-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Method Dempster, Joshua M. Boyle, Isabella Vazquez, Francisca Root, David E. Boehm, Jesse S. Hahn, William C. Tsherniak, Aviad McFarland, James M. Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects |
title | Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects |
title_full | Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects |
title_fullStr | Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects |
title_full_unstemmed | Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects |
title_short | Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects |
title_sort | chronos: a cell population dynamics model of crispr experiments that improves inference of gene fitness effects |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8686573/ https://www.ncbi.nlm.nih.gov/pubmed/34930405 http://dx.doi.org/10.1186/s13059-021-02540-7 |
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