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ReCo: automated NGS read-counting of single and combinatorial CRISPR gRNAs

SUMMARY: CRISPR screens are increasingly performed to associate genotypes with genotypes. So far, however, their analysis required specialized computational knowledge to transform high-throughput next-generation sequencing (NGS) data into sequence formats amenable for downstream analysis. We develop...

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Detalles Bibliográficos
Autores principales: Wegner, Martin, Kaulich, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10400375/
https://www.ncbi.nlm.nih.gov/pubmed/37481709
http://dx.doi.org/10.1093/bioinformatics/btad448
Descripción
Sumario:SUMMARY: CRISPR screens are increasingly performed to associate genotypes with genotypes. So far, however, their analysis required specialized computational knowledge to transform high-throughput next-generation sequencing (NGS) data into sequence formats amenable for downstream analysis. We developed ReCo, a stand-alone and user-friendly analytics tool for generating read-count tables of single and combinatorial CRISPR library and screen-based NGS data. Together with cutadapt and bowtie2 for rapid sequence trimming and alignment, ReCo enables the automated generation of read count tables from staggered NGS reads for the downstream identification of gRNA-induced phenotypes. AVAILABILITY AND IMPLEMENTATION: ReCo is published under the MIT license and available at: https://github.com/KaulichLab/ReCo.