# Modeling Functional Elements using CRISPR Screening

> **NIH NIH R01** · CHILDREN'S RESEARCH INSTITUTE · 2022 · $446,250

## Abstract

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.

## Key facts

- **NIH application ID:** 10404656
- **Project number:** 5R01HG010753-04
- **Recipient organization:** CHILDREN'S RESEARCH INSTITUTE
- **Principal Investigator:** Wei Li
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $446,250
- **Award type:** 5
- **Project period:** 2019-08-08 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10404656

## Citation

> US National Institutes of Health, RePORTER application 10404656, Modeling Functional Elements using CRISPR Screening (5R01HG010753-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10404656. Licensed CC0.

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