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An interactive web application for processing, correcting, and visualizing genome-wide pooled CRISPR-Cas9 screens.
Vinceti, Alessandro; De Lucia, Riccardo Roberto; Cremaschi, Paolo; Perron, Umberto; Karakoc, Emre; Mauri, Luca; Fernandez, Carlos; Kluczynski, Krzysztof Henryk; Anderson, Daniel Stephen; Iorio, Francesco.
Affiliation
  • Vinceti A; Computational Biology Research Centre, Human Technopole, Viale Rita Levi-Montalcini, 1, 20157 Milano, Italy.
  • De Lucia RR; Computational Biology Research Centre, Human Technopole, Viale Rita Levi-Montalcini, 1, 20157 Milano, Italy.
  • Cremaschi P; Computational Biology Research Centre, Human Technopole, Viale Rita Levi-Montalcini, 1, 20157 Milano, Italy.
  • Perron U; Computational Biology Research Centre, Human Technopole, Viale Rita Levi-Montalcini, 1, 20157 Milano, Italy.
  • Karakoc E; Cancer Dependency Map Analytics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK.
  • Mauri L; ICT and Digitalisation, Human Technopole, Viale Rita Levi-Montalcini, 1, 20157 Milano, Italy.
  • Fernandez C; ICT and Digitalisation, Human Technopole, Viale Rita Levi-Montalcini, 1, 20157 Milano, Italy.
  • Kluczynski KH; ICT and Digitalisation, Human Technopole, Viale Rita Levi-Montalcini, 1, 20157 Milano, Italy.
  • Anderson DS; ICT and Digitalisation, Human Technopole, Viale Rita Levi-Montalcini, 1, 20157 Milano, Italy.
  • Iorio F; Computational Biology Research Centre, Human Technopole, Viale Rita Levi-Montalcini, 1, 20157 Milano, Italy.
Cell Rep Methods ; 3(1): 100373, 2023 01 23.
Article in En | MEDLINE | ID: mdl-36814834
A limitation of pooled CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes arising from copy-number-amplified genomics regions. To solve this issue, we previously developed CRISPRcleanR: a computational method implemented as R/python package and in a dockerized version. CRISPRcleanR detects and corrects biased responses to CRISPR-Cas9 targeting in an unsupervised fashion, accurately reducing false-positive signals while maintaining sensitivity in identifying relevant genetic dependencies. Here, we present CRISPRcleanR WebApp , a web application enabling access to CRISPRcleanR through an intuitive interface. CRISPRcleanR WebApp removes the complexity of R/python language user interactions; provides user-friendly access to a complete analytical pipeline, not requiring any data pre-processing and generating gene-level summaries of essentiality with associated statistical scores; and offers a range of interactively explorable plots while supporting a more comprehensive range of CRISPR guide RNAs' libraries than the original package. CRISPRcleanR WebApp is available at https://crisprcleanr-webapp.fht.org/.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome / CRISPR-Cas Systems Type of study: Prognostic_studies Language: En Journal: Cell Rep Methods Year: 2023 Document type: Article Affiliation country: Italia Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome / CRISPR-Cas Systems Type of study: Prognostic_studies Language: En Journal: Cell Rep Methods Year: 2023 Document type: Article Affiliation country: Italia Country of publication: Estados Unidos