SRscore:使用元分析量化多个转录组数据集的基因应激响应的R包.
Yusuke Fukuda1, Atsushi Fukushima1,2
1Graduate School of Life and Environmental Sciences, Kyoto Prefectural University, Kyoto, Kyoto, Japan.
Genes to cells : devoted to molecular & cellular mechanisms
|February 24, 2026
概括
我们开发了SRscore,这是一款用于可再生转录组元分析的R包,用于识别应激反应基因. 这个工具简化了跨物种的分析,帮助发现基因功能.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 转录组元分析对于理解基因功能,特别是应激反应基因至关重要.
- 压力反应评分 (SRscore) 之前被开发用于使用表达变异量来量化基因应激反应.
- 以前的SRscore应用仅限于特定物种,需要专门的工具来更广泛地使用.
研究的目的:
- 推出SRscore,用于简化和可复制的转录组元分析的R包.
- 为了促进对各种物种的应激反应基因的识别和研究.
- 加强元分析输出与下游生物信息学工具的整合.
主要方法:
- 开发了SRscore R包,工作流有三个步骤:对比组配对,SRratio计算和SRscore计算.
- 包括精选的数据集和元数据处理功能,以简化分析.
- 确保与其他R/生物导体包的兼容性,用于可视化和丰富分析.
主要成果:
- 该 SRscore R 包为转录组元分析提供了一个用户友好,可重复和错误最小化的工作流.
- 该包有效计算压力反应得分 (SRscore) 和表达变化比率 (SRratio).
- SRscore的输出被设计为与现有的生物信息学分析管道无集成.
结论:
- 该SRscore R包显著推进了转录组元分析,用于应激反应基因研究.
- 该工具扩大了SRscore在物种中的适用性,并提高了基因组研究中的可重现性.
- 通过SRscore,可以更深入地了解与环境压力反应相关的基因功能.
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