Modeling Functional Elements using CRISPR Screening
Modeling Functional Elements using CRISPR Screening
批准号:
10227147
负责人:
Wei Li
金额:
$44.63万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-08 至 2024-05-31
关键词:
AddressAffectAlgorithm DesignAlgorithmic AnalysisAlgorithmsAnimal ModelBiologicalCRISPR screenCRISPR/Cas technologyCell LineCellsClustered Regularly Interspaced Short Palindromic RepeatsCodeComputational algorithmComputer AnalysisComputer ModelsComputing MethodologiesDataDevelopmentDiseaseElementsEnhancersEssential GenesGenesGeneticGenetic ScreeningGenetic studyGenome engineeringGenomicsGenotypeGoalsGuide RNAHuman GenomeInstitutesKnock-outLibrariesMethodologyMethodsModelingPaperPathway AnalysisPathway interactionsPhenotypePhysiologyPrincipal InvestigatorProteinsPublic DomainsPublishingQuality ControlRNA InterferenceResearchSeriesSoftware DesignSpecificityStatistical MethodsStatistical ModelsSupervisionSystemTechniquesTechnologyTimeUntranslated RNAVisualizationWeightWorkbasebiological systemscell typecohortcost effectivedesigngenetic predictorsgenome wide screengenome-widegraduate studentimprovedinnovationinterestknock-downknockout genemultidimensional datanovelprotein functionscreeningtranscriptome sequencing
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Project Summary
The recent development of genome-wide CRISPR/Cas9 screening technology (“CRISPR screens”)
identifies functional genes associated with phenotype of interest in a fast and high-throughput manner.
Besides protein-coding genes, novel screening techniques enable the functional interrogation of non-
coding elements and genetic interactions. We have developed a series of computational algorithms and
softwares for the design, quality control, analysis, visualization and interpretation of CRISPR screens.
Among these, the MAGeCK/MAGeCK-VISPR algorithms have been widely used for analyzing
screening data.
In this proposal, we aim to develop the statistical and computational models to improve the functional
interrogation of protein-coding genes, and to extend it to study non-coding elements and genetic
interactions. Specifically, we propose to: Aim 1. Improve functional gene identification from CRISPR
screens, from integrating screening data from heterogenous background and viewing the data in a
pathway manner; Aim 2. Develop the design and analysis algorithms for non-coding CRISPR functional
studies, and predict functional enhancers across various cell types. Aim 3. Study genetic interactions
from CRISPR screens targeting gene pairs, by modeling this novel type of screening data.
At the conclusion of these studies, we will have developed several analysis algorithms for CRISPR
screens of various types, facilitating the functional studies of genes, non-coding elements and genetic
interactions. These algorithms will be made easy and convenient for experimental biologists to answer
important biological questions about the functions of protein-coding genes, non-coding elements and
genetic interactions.
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