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PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens

Large-scale genetic screens using CRISPR/Cas9 technology have emerged as a major tool for functional genomics. With its increased popularity, experimental biologists frequently acquire large sequencing datasets for which they often do not have an easy analysis option. While a few bioinformatic tools...

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Autores principales: Spahn, Philipp N., Bath, Tyler, Weiss, Ryan J., Kim, Jihoon, Esko, Jeffrey D., Lewis, Nathan E., Harismendy, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5696473/
https://www.ncbi.nlm.nih.gov/pubmed/29158538
http://dx.doi.org/10.1038/s41598-017-16193-9
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author Spahn, Philipp N.
Bath, Tyler
Weiss, Ryan J.
Kim, Jihoon
Esko, Jeffrey D.
Lewis, Nathan E.
Harismendy, Olivier
author_facet Spahn, Philipp N.
Bath, Tyler
Weiss, Ryan J.
Kim, Jihoon
Esko, Jeffrey D.
Lewis, Nathan E.
Harismendy, Olivier
author_sort Spahn, Philipp N.
collection PubMed
description Large-scale genetic screens using CRISPR/Cas9 technology have emerged as a major tool for functional genomics. With its increased popularity, experimental biologists frequently acquire large sequencing datasets for which they often do not have an easy analysis option. While a few bioinformatic tools have been developed for this purpose, their utility is still hindered either due to limited functionality or the requirement of bioinformatic expertise. To make sequencing data analysis of CRISPR/Cas9 screens more accessible to a wide range of scientists, we developed a Platform-independent Analysis of Pooled Screens using Python (PinAPL-Py), which is operated as an intuitive web-service. PinAPL-Py implements state-of-the-art tools and statistical models, assembled in a comprehensive workflow covering sequence quality control, automated sgRNA sequence extraction, alignment, sgRNA enrichment/depletion analysis and gene ranking. The workflow is set up to use a variety of popular sgRNA libraries as well as custom libraries that can be easily uploaded. Various analysis options are offered, suitable to analyze a large variety of CRISPR/Cas9 screening experiments. Analysis output includes ranked lists of sgRNAs and genes, and publication-ready plots. PinAPL-Py helps to advance genome-wide screening efforts by combining comprehensive functionality with user-friendly implementation. PinAPL-Py is freely accessible at http://pinapl-py.ucsd.edu with instructions and test datasets.
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spelling pubmed-56964732017-11-29 PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens Spahn, Philipp N. Bath, Tyler Weiss, Ryan J. Kim, Jihoon Esko, Jeffrey D. Lewis, Nathan E. Harismendy, Olivier Sci Rep Article Large-scale genetic screens using CRISPR/Cas9 technology have emerged as a major tool for functional genomics. With its increased popularity, experimental biologists frequently acquire large sequencing datasets for which they often do not have an easy analysis option. While a few bioinformatic tools have been developed for this purpose, their utility is still hindered either due to limited functionality or the requirement of bioinformatic expertise. To make sequencing data analysis of CRISPR/Cas9 screens more accessible to a wide range of scientists, we developed a Platform-independent Analysis of Pooled Screens using Python (PinAPL-Py), which is operated as an intuitive web-service. PinAPL-Py implements state-of-the-art tools and statistical models, assembled in a comprehensive workflow covering sequence quality control, automated sgRNA sequence extraction, alignment, sgRNA enrichment/depletion analysis and gene ranking. The workflow is set up to use a variety of popular sgRNA libraries as well as custom libraries that can be easily uploaded. Various analysis options are offered, suitable to analyze a large variety of CRISPR/Cas9 screening experiments. Analysis output includes ranked lists of sgRNAs and genes, and publication-ready plots. PinAPL-Py helps to advance genome-wide screening efforts by combining comprehensive functionality with user-friendly implementation. PinAPL-Py is freely accessible at http://pinapl-py.ucsd.edu with instructions and test datasets. Nature Publishing Group UK 2017-11-20 /pmc/articles/PMC5696473/ /pubmed/29158538 http://dx.doi.org/10.1038/s41598-017-16193-9 Text en © The Author(s) 2017 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Spahn, Philipp N.
Bath, Tyler
Weiss, Ryan J.
Kim, Jihoon
Esko, Jeffrey D.
Lewis, Nathan E.
Harismendy, Olivier
PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens
title PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens
title_full PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens
title_fullStr PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens
title_full_unstemmed PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens
title_short PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens
title_sort pinapl-py: a comprehensive web-application for the analysis of crispr/cas9 screens
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5696473/
https://www.ncbi.nlm.nih.gov/pubmed/29158538
http://dx.doi.org/10.1038/s41598-017-16193-9
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