CRISPulator: a discrete simulation tool for pooled genetic screens
Abstract Background The rapid adoption of CRISPR technology has enabled biomedical researchers to conduct CRISPR-based genetic screens in a pooled format. The quality of results from such screens is heavily dependent on the selection of optimal screen design parameters, which also affects cost and s...
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doaj-14916f21d3214d72896d4032c14f97072020-11-25T00:35:17ZengBMCBMC Bioinformatics1471-21052017-07-0118111210.1186/s12859-017-1759-9CRISPulator: a discrete simulation tool for pooled genetic screensTamas Nagy0Martin Kampmann1Graduate program in Bioinformatics, University of CaliforniaDepartment of Biochemistry and Biophysics, Institute for Neurodegenerative Diseases and California Institute for Quantitative Biomedical Research, University of CaliforniaAbstract Background The rapid adoption of CRISPR technology has enabled biomedical researchers to conduct CRISPR-based genetic screens in a pooled format. The quality of results from such screens is heavily dependent on the selection of optimal screen design parameters, which also affects cost and scalability. However, the cost and effort of implementing pooled screens prohibits experimental testing of a large number of parameters. Results We present CRISPulator, a Monte Carlo method-based computational tool that simulates the impact of screen parameters on the robustness of screen results, thereby enabling users to build intuition and insights that will inform their experimental strategy. CRISPulator enables the simulation of screens relying on either CRISPR interference (CRISPRi) or CRISPR nuclease (CRISPRn). Pooled screens based on cell growth/survival, as well as fluorescence-activated cell sorting according to fluorescent reporter phenotypes are supported. CRISPulator is freely available online ( http://crispulator.ucsf.edu ). Conclusions CRISPulator facilitates the design of pooled genetic screens by enabling the exploration of a large space of experimental parameters in silico, rather than through costly experimental trial and error. We illustrate its power by deriving non-obvious rules for optimal screen design.http://link.springer.com/article/10.1186/s12859-017-1759-9CRISPRCRISPRiFunctional genomicsGenome-wide screensSimulationMonte Carlo |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tamas Nagy Martin Kampmann |
spellingShingle |
Tamas Nagy Martin Kampmann CRISPulator: a discrete simulation tool for pooled genetic screens BMC Bioinformatics CRISPR CRISPRi Functional genomics Genome-wide screens Simulation Monte Carlo |
author_facet |
Tamas Nagy Martin Kampmann |
author_sort |
Tamas Nagy |
title |
CRISPulator: a discrete simulation tool for pooled genetic screens |
title_short |
CRISPulator: a discrete simulation tool for pooled genetic screens |
title_full |
CRISPulator: a discrete simulation tool for pooled genetic screens |
title_fullStr |
CRISPulator: a discrete simulation tool for pooled genetic screens |
title_full_unstemmed |
CRISPulator: a discrete simulation tool for pooled genetic screens |
title_sort |
crispulator: a discrete simulation tool for pooled genetic screens |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2017-07-01 |
description |
Abstract Background The rapid adoption of CRISPR technology has enabled biomedical researchers to conduct CRISPR-based genetic screens in a pooled format. The quality of results from such screens is heavily dependent on the selection of optimal screen design parameters, which also affects cost and scalability. However, the cost and effort of implementing pooled screens prohibits experimental testing of a large number of parameters. Results We present CRISPulator, a Monte Carlo method-based computational tool that simulates the impact of screen parameters on the robustness of screen results, thereby enabling users to build intuition and insights that will inform their experimental strategy. CRISPulator enables the simulation of screens relying on either CRISPR interference (CRISPRi) or CRISPR nuclease (CRISPRn). Pooled screens based on cell growth/survival, as well as fluorescence-activated cell sorting according to fluorescent reporter phenotypes are supported. CRISPulator is freely available online ( http://crispulator.ucsf.edu ). Conclusions CRISPulator facilitates the design of pooled genetic screens by enabling the exploration of a large space of experimental parameters in silico, rather than through costly experimental trial and error. We illustrate its power by deriving non-obvious rules for optimal screen design. |
topic |
CRISPR CRISPRi Functional genomics Genome-wide screens Simulation Monte Carlo |
url |
http://link.springer.com/article/10.1186/s12859-017-1759-9 |
work_keys_str_mv |
AT tamasnagy crispulatoradiscretesimulationtoolforpooledgeneticscreens AT martinkampmann crispulatoradiscretesimulationtoolforpooledgeneticscreens |
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