CoGTEx:从GTEx数据预测新型功能基因合作伙伴的未缩放的系统级共表达估计
Miguel-Angel Cortes-Guzman1, Víctor Treviño1,2
1Tecnologico de Monterrey, Escuela de Medicina, Bioinformática, Monterrey, Nuevo León, México.
PloS one
|October 4, 2024
概括
我们介绍了系统层面的协同表达分析,这是一种新的方法,它考虑了所有基因表达数据而没有组织标准化. 这种方法揭示了有价值的生物学见解,可以通过CoGTEx资源访问.
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.
- 系统生物学 系统生物学
背景情况:
- 同表达分析对于理解生物途径,基因调节和人类疾病至关重要.
- 目前的协同表达估计通常依赖于组织水平的标准化,可能会忽视来自整体基因表达水平的有价值信息.
- 需要采用结合多种细胞类型并考虑组织间不统一的数据的协同表达方法.
研究的目的:
- 在共同表达分析中,挑战差异比平均基因表达水平更重要这一假设.
- 开发和验证不依赖于组织标准化的"系统级"协同表达估计方法.
- 为从人类GTEx数据中探索组织层面和系统层面的共同表达数据提供一个全面的资源.
主要方法:
- GTEx v8表达数据经历了全球规范化,批处理和过.
- 主要组件分析 (PCA),集群和t分布式静态邻居嵌入 (tSNE) 用于定义42个不同的组织集群.
- 计算了42个组织群中的33445个基因的同表达,使用抽样来避免组织过度代表,并重复20次以获得可靠的估计. 皮尔森,斯皮尔曼和G统计指标在系统层面 (TPM尺度) 和组织层面 (z-score尺度) 计算.
主要成果:
- 根据现有数据库验证了组织水平的协同表达估计.
- 系统水平的协同表达估计与组织水平的估计有所不同,两者都揭示了关于生物通路的宝贵信息.
- 发现同表达估计与转录调节有关,并提出了CoGTEx资源,用于分析人类成年组织同表达数据.
结论:
- 系统层面的共同表达代表了产生生物假设和预测的新和有价值的指标.
- CoGTEx资源提供了一个独特的平台,可以查看,比较和下载系统和组织水平的协同表达估计.
- 这项研究强调了在联合表达分析中考虑整体基因表达水平的重要性,以更全面地了解生物系统.
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