# Modeling Heterogenous Outcomes in Functional Genetic Screens Using Single-cell Genomics as Readouts

> **NIH NIH R01** · CHILDREN'S RESEARCH INSTITUTE · 2023 · $268,752

## Abstract

Modeling Heterogenous Outcomes in Functional Genetic Screens Using Single-cell Genomics as
Readouts
This supplementary request seeks to advance the analysis of single-cell CRISPR screening datasets by
developing novel computational models to address the challenge of heterogeneous transcriptome responses
upon perturbing the same gene. It falls within the scope of the parent award to develop algorithms for
functional genetic screens, but proposes to follow up on unanticipated results (single-cell CRISPR screen) and
enhance this direction, which is unexpectedly productive, as is demonstrated in preliminary results.
Specifically, we aim to: (1) build a model to detect heterogeneous expression patterns in Perturb-seq assays, l,
and (2) extend the model to other dataset types, including pooled single-cell and bulk transcriptomics datasets
from various gene perturbations. This work will significantly enhance our understanding of genotype-phenotype
relationships at the single-cell level, with broad applications in cancer research, virology, and gene regulation.

## Key facts

- **NIH application ID:** 10837914
- **Project number:** 3R01HG010753-05S1
- **Recipient organization:** CHILDREN'S RESEARCH INSTITUTE
- **Principal Investigator:** Wei Li
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $268,752
- **Award type:** 3
- **Project period:** 2019-08-08 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10837914

## Citation

> US National Institutes of Health, RePORTER application 10837914, Modeling Heterogenous Outcomes in Functional Genetic Screens Using Single-cell Genomics as Readouts (3R01HG010753-05S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10837914. Licensed CC0.

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