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探索分析前变量对基因表达测量和癌症研究中的相对表达顺序的影响
Tian Tian1,2, Guie Lai3, Ming He1
1Medical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Scientific reports
|February 6, 2025
概括
分析前的变量可以影响基因表达测量,但基因对的相对表达顺序 (REO) 仍然很强大. 这一发现支持在转录学研究中使用REO进行可靠的生物标志物发现.
科学领域:
- 文字转录学 (Transcriptomics) 是一个学科.
- 生物标志物发现发现
- 分子生物学分子生物学
背景情况:
- 基因表达特征分析对于识别生物标志物至关重要.
- 预分析变量在基因表达测量中引入不确定性和错误.
- 需要对这些变量对基因表达和相对表达顺序 (REO) 的影响进行系统评估.
研究的目的:
- 评估各种预分析变量的对基因表达测量和REO的影响.
- 为了确定REO在分析前变化的稳定性.
- 评估基于REO的方法对生物标志物研究的潜力.
主要方法:
- 使用了18个数据集,有800多个配对样本 (案例:低质量,控制:高质量).
- 采样方法,异质性,时间延迟,保存,降解,套件,RNA数量,平台和实验室地点的评估影响.
- 分析了单个和多变量对基因表达和REO的影响.
主要成果:
- 成千上万的基因在低质量和高质量样本之间显示了双重表达变化.
- 平均而言,82% (单变量) 和76% (多变量) 的基因对保持了一致的REO.
- 在分析前的变化下,REOs显示出比单个基因表达测量更高的稳定性.
结论:
- 相对表达式排序 (REO) 对预分析变量具有稳定性.
- 基于REO的方法显示出可靠的转录组学和生物标志物研究的巨大潜力.
- 这种稳定性提高了REO在各种生物和临床研究环境中的实用性.
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