# Resolving single-cell analysis challenges via data-driven decision frameworks and novel statistical methods

> **NIH NIH R35** · UNIVERSITY OF FLORIDA · 2022 · $372,971

## Abstract

Resolving single-cell analysis challenges via data-driven decision frameworks and novel statistical
methods
Abstract:
Despite the power of single-cell RNA-seq, the data presents a multitude of analytical challenges and
researchers continue to struggle with data analysis. The long-term goals of this research program are to
develop robust, efficient, and scalable statistical methods and tools that enable all scientists to obtain accurate
biological inferences. Specifically, we propose to develop interactive data-driven decision-frameworks to guide
researchers through analyses and make informed analytical decisions. We also propose developing methods
that retain interpretability while accommodating complex experimental designs. All of our approaches will be
developed as highly accessible statistical software with interactive visualization and analysis modules available
via webservers. Our proposed methods will result in richer analyses and biological insights, as well as,
improved reproducibility and reliability of scientific results.

## Key facts

- **NIH application ID:** 10499141
- **Project number:** 1R35GM146895-01
- **Recipient organization:** UNIVERSITY OF FLORIDA
- **Principal Investigator:** Rhonda Bacher
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $372,971
- **Award type:** 1
- **Project period:** 2022-09-21 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10499141

## Citation

> US National Institutes of Health, RePORTER application 10499141, Resolving single-cell analysis challenges via data-driven decision frameworks and novel statistical methods (1R35GM146895-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10499141. Licensed CC0.

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