PoweREST:空间转录组学实验的统计功率估计,用于检测两个条件之间的差异表达基因
Lan Shui1, Anirban Maitra2, Ying Yuan1
1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
PLoS computational biology
|July 29, 2025
概括
高成本限制了空间转录学 (ST) 的应用. 我们开发了PoweREST,这是使用10X Genomics Visium数据进行差异基因表达分析的功率计算工具,增强了ST研究设计.
科学领域:
- 基因组学和分子生物学
- 生物信息学和计算生物学
背景情况:
- 空间转录学 (ST) 的进步提供了强大的生物学见解.
- 科学和技术数据生成的高成本限制了广泛的研究应用.
- 强大的统计能力对于最大限度地利用有限的ST数据至关重要.
研究的目的:
- 解决ST中差异性基因表达 (DEG) 分析功率计算方法缺乏的问题.
- 介绍PoweREST,用于估计ST研究中的统计功率的工具.
- 为ST研究提供知情的实验设计和资源分配.
主要方法:
- 开发PoweREST,一个专门用于10X Genomics Visium ST数据的功率估计工具.
- PoweREST支持在实验前和初步数据收集后进行功率计算.
- 一个用户友好的,无程序的网络应用程序,用于交互式功率分析和可视化.
主要成果:
- PoweREST提供了一种计算ST数据中DEG检测的统计功率的方法.
- 该工具使研究人员能够评估ST实验的可行性和优化参数.
- 交互式可视化有助于理解权力和研究参数之间的关系.
结论:
- PoweREST解决了在空间转录学DEG研究中对功率分析的关键需求.
- 该工具提高了ST研究的统计稳定性和成本效益.
- 有助于更好地规划和解释空间转录组学实验.
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