Quality control, modeling, and visualization of CRISPR screens with MAGeCK-VISPR
Контроль качества, моделирование и визуализация CRISPR-скринингов с помощью MAGeCK-VISPR
2015-12-01
SCID: 54.1/fng86wut
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CRISPR screensMAGeCK-VISPRgeneralized linear modelmaximum-likelihood algorithmquality control
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Abstract (AI)
High-throughput CRISPR screens have shown great promise in functional genomics. We present MAGeCK-VISPR, a comprehensive quality control (QC), analysis, and visualization workflow for CRISPR screens. MAGeCK-VISPR defines a set of QC measures to assess the quality of an experiment, and includes a maximum-likelihood algorithm to call essential genes simultaneously under multiple conditions. The algorithm uses a generalized linear model to deconvolute different effects, and employs expectation-maximization to iteratively estimate sgRNA knockout efficiency and gene essentiality. MAGeCK-VISPR also includes VISPR, a framework for the interactive visualization and exploration of QC and analysis results. MAGeCK-VISPR is freely available at http://bitbucket.org/liulab/mageck-vispr .
Key Findings
1
A generalized linear model separates different experimental effects, while expectation-maximization jointly estimates sgRNA knockout efficiency and gene essentiality.
2
Its maximum-likelihood algorithm identifies essential genes simultaneously across multiple experimental conditions.
3
MAGeCK-VISPR provides an integrated workflow for quality control, analysis, and visualization of high-throughput CRISPR screens.
4
The workflow defines quality-control measures for assessing CRISPR screening experiment quality.
5
VISPR enables interactive visualization and exploration of CRISPR screen quality-control and analysis results.
Research Object
high-throughput CRISPR screens
Research Subject
quality control, analysis, modeling, and visualization of screen results, including condition-specific gene essentiality and sgRNA knockout efficiency
Publication Details
Publication Date
2015-12-01
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