Computational Methods for Genome-Wide CRISPR Screens

全基因组 CRISPR 筛选的计算方法

• 批准号: 9350386
• 负责人: Xiaole Shirley Liu
• 金额: $ 51.91万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-09 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9350386
• 关键词: Adopted; Adoption; Algorithmic Analysis; Algorithms; Behavior; Bioinformatics; Biological; Biological Markers; Biological Process; Biology; CRISPR interference; CRISPR screen; Cell Line; Cells; Clustered Regularly Interspaced Short Palindromic Repeats; Communities; Computer Analysis; Computer Simulation; Computer software; Computing Methodologies; Custom; DNA Sequence; Data; Data Analyses; Development; Disease; Drug resistance; Essential Genes; Evaluation; Experimental Designs; Gene Expression; Gene Expression Regulation; Generations; Genes; Genomics; Goals; Guide RNA; Imagery; Knock-out; Label; Libraries; Mammalian Cell; Methodology; Methods; Modeling; Pathway interactions; Performance; Pharmaceutical Preparations; Phenotype; Physiological Processes; Proteins; Publishing; Quality Control; Regulator Genes; Research; Somatic Cell; Sorting - Cell Movement; Statistical Methods; Statistical Models; System; Techniques; Technology; Time; Validation; Work; base; cell growth; cell motility; computer framework; cost effective; data visualization; design; experimental study; genetic analysis; genome editing; genome-wide; genome-wide analysis; improved; interest; migration; novel; prototype; public health relevance; response; screening; small hairpin RNA; stem cell differentiation; tumorigenesis; user friendly software; user-friendly

 DESCRIPTION (provided by applicant): The CRISPR/Cas9 system is a revolutionary approach for genome editing of mammalian cells. Recent developments in CRISPR/Cas9 knockout technology as well as dCas9 fused with effector proteins enable high throughput cost-effective gene functional screens but create computational challenges. We have developed a Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout (MAGeCK) method for calling genes and pathways from genome-scale CRISPR/Cas9 screens. MAGeCK demonstrates better performance than previous methods and identify robust hits, including novel ones, from several published screens. In this proposal, we aim to develop the statistical and computational methods to improve the MAGeCK algorithm to enable quality control, data analysis, and interactive visualizations of CRISPR screen data. In one unified statistical model, the proposed method corrects batch effect at gRNA level, simultaneously estimates gRNA efficiency and gene selection, and identifies differential gene and pathway selection over multiple conditions, and considers sequencing bias and cell doubling time. Specifically, we propose to: Aim 1. Develop robust data normalization methods for CRISPR screens. Aim 2. Develop the statistical and computational framework to call cell- and condition-specific essential genes and pathways from multiple CRISPR screen experiments and conditions. Aim 3. Develop methods to mitigate outlier gRNA effects and use protein interaction network to enhance the performance of CRISPR screen gene calling. Aim 4. Develop user-friendly software features, such as quality control, visualization, design and analysis software for CRISPR screens. At the conclusion of these studies, we will have developed more versatile and reliable analysis algorithms for CRISPR screens under diverse experimental settings. These methods could be applied to CRISPR knockout screens, CRISPRi/a screens, sequencing-based si/shRNA screens, and the phenotype could be cell growth, migration, differentiation, or sorting of GFP-labeled gene expression. Our proposed methods will greatly facilitate the technology adoption to many experimental biology groups, so they can use the powerful genome-wide CRISPR screens under diverse experimental settings to answer important biological questions about gene regulation and drug response.

 描述（由适用提供）：CRISPR/CAS9系统是哺乳动物细胞基因组编辑的革命性方法。 CRISPR/CAS9敲除技术以及与效应蛋白融合的DCAS9的最新发展使高吞吐量具有成本效益的基因功能筛选，但会引起计算挑战。我们已经开发了基于基因组CRISPR/CAS9敲除（MAGECK）方法的基于模型的分析，用于调用基因组尺度CRISPR/CAS9屏幕的基因和途径。玛格克（Mageck）表现出比以前的方法更好的性能，并从几个已发表的屏幕中识别出强大的命中，包括新颖的命中。在此建议中，我们旨在开发统计和计算方法来改进Mageck算法，以实现CRISPR屏幕数据的质量控制，数据分析和交互式可视化。在一个统一的统计模型中，该提出的方法在GRNA水平上纠正了批处理效应，同时估计了GRNA效率和基因选择，并在多种条件下鉴定了差异基因和途径选择，并考虑了测序偏置和细胞配音时间。具体来说，我们建议：目标1。为CRISPR屏幕开发可靠的数据归一化方法。 AIM 2。开发统计和计算框架，从多个CRISPR屏幕实验和条件中调用细胞和条件特定的基本基因和途径。 AIM 3。开发方法来减轻离群值效应并使用蛋白质相互作用网络来增强CRISPR屏幕基因调用的性能。 AIM 4。开发用户友好的软件功能，例如CRISPR屏幕的质量控制，可视化，设计和分析软件。这些研究结束时，在潜水员实验环境下，我们将为CRISPR屏幕开发更通用和可靠的分析算法。这些方法可以应用于CRISPR敲除屏幕，CRISPRI/A筛选，基于测序的SI/SHRNA筛选，表型可以是细胞的生长，迁移，分化或GFP标记基因表达的分类。我们提出的方法将极大地支持许多实验生物学组的技术采用，因此他们可以在潜水员实验环境下使用强大的全基因组CRISPR筛选来回答有关基因调节和药物反应的重要生物学问题。