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CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens

BACKGROUND: CRISPR-Cas9 genome-wide screens are being increasingly performed, allowing systematic explorations of cancer dependencies at unprecedented accuracy and scale. One of the major computational challenges when analysing data derived from such screens is to identify genes that are essential f...

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Autores principales: Vinceti, Alessandro, Karakoc, Emre, Pacini, Clare, Perron, Umberto, De Lucia, Riccardo Roberto, Garnett, Mathew J., Iorio, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8597285/
https://www.ncbi.nlm.nih.gov/pubmed/34789150
http://dx.doi.org/10.1186/s12864-021-08129-5
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author Vinceti, Alessandro
Karakoc, Emre
Pacini, Clare
Perron, Umberto
De Lucia, Riccardo Roberto
Garnett, Mathew J.
Iorio, Francesco
author_facet Vinceti, Alessandro
Karakoc, Emre
Pacini, Clare
Perron, Umberto
De Lucia, Riccardo Roberto
Garnett, Mathew J.
Iorio, Francesco
author_sort Vinceti, Alessandro
collection PubMed
description BACKGROUND: CRISPR-Cas9 genome-wide screens are being increasingly performed, allowing systematic explorations of cancer dependencies at unprecedented accuracy and scale. One of the major computational challenges when analysing data derived from such screens is to identify genes that are essential for cell survival invariantly across tissues, conditions, and genomic-contexts (core-fitness genes), and to distinguish them from context-specific essential genes. This is of paramount importance to assess the safety profile of candidate therapeutic targets and for elucidating mechanisms involved in tissue-specific genetic diseases. RESULTS: We have developed CoRe: an R package implementing existing and novel methods for the identification of core-fitness genes (at two different level of stringency) from joint analyses of multiple CRISPR-Cas9 screens. We demonstrate, through a fully reproducible benchmarking pipeline, that CoRe outperforms state-of-the-art tools, yielding more reliable and biologically relevant sets of core-fitness genes. CONCLUSIONS: CoRe offers a flexible pipeline, compatible with many pre-processing methods for the analysis of CRISPR data, which can be tailored onto different use-cases. The CoRe package can be used for the identification of high-confidence novel core-fitness genes, as well as a means to filter out potentially cytotoxic hits while analysing cancer dependency datasets for identifying and prioritising novel selective therapeutic targets. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-08129-5.
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spelling pubmed-85972852021-11-17 CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens Vinceti, Alessandro Karakoc, Emre Pacini, Clare Perron, Umberto De Lucia, Riccardo Roberto Garnett, Mathew J. Iorio, Francesco BMC Genomics Software BACKGROUND: CRISPR-Cas9 genome-wide screens are being increasingly performed, allowing systematic explorations of cancer dependencies at unprecedented accuracy and scale. One of the major computational challenges when analysing data derived from such screens is to identify genes that are essential for cell survival invariantly across tissues, conditions, and genomic-contexts (core-fitness genes), and to distinguish them from context-specific essential genes. This is of paramount importance to assess the safety profile of candidate therapeutic targets and for elucidating mechanisms involved in tissue-specific genetic diseases. RESULTS: We have developed CoRe: an R package implementing existing and novel methods for the identification of core-fitness genes (at two different level of stringency) from joint analyses of multiple CRISPR-Cas9 screens. We demonstrate, through a fully reproducible benchmarking pipeline, that CoRe outperforms state-of-the-art tools, yielding more reliable and biologically relevant sets of core-fitness genes. CONCLUSIONS: CoRe offers a flexible pipeline, compatible with many pre-processing methods for the analysis of CRISPR data, which can be tailored onto different use-cases. The CoRe package can be used for the identification of high-confidence novel core-fitness genes, as well as a means to filter out potentially cytotoxic hits while analysing cancer dependency datasets for identifying and prioritising novel selective therapeutic targets. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-08129-5. BioMed Central 2021-11-17 /pmc/articles/PMC8597285/ /pubmed/34789150 http://dx.doi.org/10.1186/s12864-021-08129-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Vinceti, Alessandro
Karakoc, Emre
Pacini, Clare
Perron, Umberto
De Lucia, Riccardo Roberto
Garnett, Mathew J.
Iorio, Francesco
CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens
title CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens
title_full CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens
title_fullStr CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens
title_full_unstemmed CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens
title_short CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens
title_sort core: a robustly benchmarked r package for identifying core-fitness genes in genome-wide pooled crispr-cas9 screens
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8597285/
https://www.ncbi.nlm.nih.gov/pubmed/34789150
http://dx.doi.org/10.1186/s12864-021-08129-5
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