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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
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author Wegner, Martin
Kaulich, Manuel
author_facet Wegner, Martin
Kaulich, Manuel
author_sort Wegner, Martin
collection PubMed
description 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.
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spelling pubmed-104003752023-08-05 ReCo: automated NGS read-counting of single and combinatorial CRISPR gRNAs Wegner, Martin Kaulich, Manuel Bioinformatics Applications Note 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. Oxford University Press 2023-07-22 /pmc/articles/PMC10400375/ /pubmed/37481709 http://dx.doi.org/10.1093/bioinformatics/btad448 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Wegner, Martin
Kaulich, Manuel
ReCo: automated NGS read-counting of single and combinatorial CRISPR gRNAs
title ReCo: automated NGS read-counting of single and combinatorial CRISPR gRNAs
title_full ReCo: automated NGS read-counting of single and combinatorial CRISPR gRNAs
title_fullStr ReCo: automated NGS read-counting of single and combinatorial CRISPR gRNAs
title_full_unstemmed ReCo: automated NGS read-counting of single and combinatorial CRISPR gRNAs
title_short ReCo: automated NGS read-counting of single and combinatorial CRISPR gRNAs
title_sort reco: automated ngs read-counting of single and combinatorial crispr grnas
topic Applications Note
url 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
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