TY - JOUR
T1 - CRISPR-Analytics (CRISPR-A)
T2 - A platform for precise analytics and simulations for gene editing
AU - Sanvicente-Garcia, Marta
AU - Garcia-Valiente, Albert
AU - Jouide, Socayna
AU - Jaraba-Wallace, Jessica
AU - Bautista, Eric
AU - Escobosa, Marc
AU - Sanchez-Mejias, Avencia
AU - Guell, Marc
PY - 2023
Y1 - 2023
N2 - Gene editing characterization with currently available tools does not always give precise relative proportions among the different types of gene edits present in an edited bulk of cells. We have developed CRISPR-Analytics, CRISPR-A, which is a comprehensive and versatile genome editing web application tool and a nextflow pipeline to give support to gene editing experimental design and analysis. CRISPR-A provides a robust gene editing analysis pipeline composed of data analysis tools and simulation. It achieves higher accuracy than current tools and expands the functionality. The analysis includes mock-based noise correction, spike-in calibrated amplification bias reduction, and advanced interactive graphics. This expanded robustness makes this tool ideal for analyzing highly sensitive cases such as clinical samples or experiments with low editing efficiencies. It also provides an assessment of experimental design through the simulation of gene editing results. Therefore, CRISPR-A is ideal to support multiple kinds of experiments such as double-stranded DNA break-based engineering, base editing (BE), primer editing (PE), and homology-directed repair (HDR), without the need of specifying the used experimental approach. Author summaryPrecision and accuracy are paramount for genome editing usage in sensitive applications such as clinical. This field requires reliable and traceable results to ensure the safety and viability of the resulting genomic modifications. To go in this direction, we have developed a computational platform that can simulate and analyze genome editing outcomes comprehensively and in a versatile manner. Our computational pipeline and web application, CRISPR-Analytics (CRISPR-A), expands the functionality of currently available tools. The added robustness of our tool makes it perfect for analyzing sensitive data, such as clinical samples or experiments with low editing efficiencies.
AB - Gene editing characterization with currently available tools does not always give precise relative proportions among the different types of gene edits present in an edited bulk of cells. We have developed CRISPR-Analytics, CRISPR-A, which is a comprehensive and versatile genome editing web application tool and a nextflow pipeline to give support to gene editing experimental design and analysis. CRISPR-A provides a robust gene editing analysis pipeline composed of data analysis tools and simulation. It achieves higher accuracy than current tools and expands the functionality. The analysis includes mock-based noise correction, spike-in calibrated amplification bias reduction, and advanced interactive graphics. This expanded robustness makes this tool ideal for analyzing highly sensitive cases such as clinical samples or experiments with low editing efficiencies. It also provides an assessment of experimental design through the simulation of gene editing results. Therefore, CRISPR-A is ideal to support multiple kinds of experiments such as double-stranded DNA break-based engineering, base editing (BE), primer editing (PE), and homology-directed repair (HDR), without the need of specifying the used experimental approach. Author summaryPrecision and accuracy are paramount for genome editing usage in sensitive applications such as clinical. This field requires reliable and traceable results to ensure the safety and viability of the resulting genomic modifications. To go in this direction, we have developed a computational platform that can simulate and analyze genome editing outcomes comprehensively and in a versatile manner. Our computational pipeline and web application, CRISPR-Analytics (CRISPR-A), expands the functionality of currently available tools. The added robustness of our tool makes it perfect for analyzing sensitive data, such as clinical samples or experiments with low editing efficiencies.
U2 - 10.1371/journal.pcbi.1011137
DO - 10.1371/journal.pcbi.1011137
M3 - Journal article
C2 - 37253059
SN - 1553-734X
VL - 19
JO - PLOS Computational Biology
JF - PLOS Computational Biology
IS - 5
M1 - e1011137
ER -