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

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          Abstract

          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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          Genetic screens and functional genomics using CRISPR/Cas9 technology.

          Functional genomics attempts to understand the genome by perturbing the flow of information from DNA to RNA to protein, in order to learn how gene dysfunction leads to disease. CRISPR/Cas9 technology is the newest tool in the geneticist's toolbox, allowing researchers to edit DNA with unprecedented ease, speed and accuracy, and representing a novel means to perform genome-wide genetic screens to discover gene function. In this review, we first summarize the discovery and characterization of CRISPR/Cas9, and then compare it to other genome engineering technologies. We discuss its initial use in screening applications, with a focus on optimizing on-target activity and minimizing off-target effects. Finally, we comment on future challenges and opportunities afforded by this technology.
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            caRpools: an R package for exploratory data analysis and documentation of pooled CRISPR/Cas9 screens

            Genetic screens by CRISPR/Cas9-mediated genome engineering have become a powerful tool for functional genomics. However, there is currently a lack of end-to-end software pipelines to analyze CRISPR/Cas9 screens based on next generation sequencing.
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              CRISPR-Cas9 for medical genetic screens: applications and future perspectives.

              CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats-CRISPR associated nuclease 9) systems have emerged as versatile and convenient (epi)genome editing tools and have become an important player in medical genetic research. CRISPR-Cas9 and its variants such as catalytically inactivated Cas9 (dead Cas9, dCas9) and scaffold-incorporating single guide sgRNA (scRNA) have been applied in various genomic screen studies. CRISPR screens enable high-throughput interrogation of gene functions in health and diseases. Compared with conventional RNAi screens, CRISPR screens incur less off-target effects and are more versatile in that they can be used in multiple formats such as knockout, knockdown and activation screens, and can target coding and non-coding regions throughout the genome. This powerful screen platform holds the potential of revolutionising functional genomic studies in the near future. Herein, we introduce the mechanisms of (epi)genome editing mediated by CRISPR-Cas9 and its variants, introduce the procedures and applications of CRISPR screen in functional genomics, compare it with conventional screen tools and at last discuss current challenges and opportunities and propose future directions.
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                Author and article information

                Contributors
                n4lewis@ucsd.edu
                oharismendy@ucsd.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                20 November 2017
                20 November 2017
                2017
                : 7
                : 15854
                Affiliations
                [1 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, School of Medicine, Department of Pediatrics, University of California San Diego, ; La Jolla, CA USA
                [2 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Novo Nordisk Foundation Center for Biosustainability at UCSD, University of California San Diego, ; La Jolla, CA USA
                [3 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Glycobiology Research and Training Center, Department of Cellular and Molecular Medicine, University of California San Diego, ; La Jolla, CA USA
                [4 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Division of Biomedical Informatics, University of California San Diego, ; La Jolla, CA USA
                [5 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Moores Cancer Center, Department of Medicine, University of California San Diego, ; La Jolla, CA USA
                Article
                16193
                10.1038/s41598-017-16193-9
                5696473
                29158538
                7fc0c4d5-1fd3-4c80-9ea8-22efe4f84934
                © 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/.

                History
                : 31 August 2017
                : 8 November 2017
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