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转录组学的生成和整合建模,使用甲固态抛嵌入材料

Eliseos J Mucaki¹, Wenhan Zhang¹, Aryamaan Saha²

¹Department of Biochemistry, Western University, 1151 Richmond St., London, ON, N6A 3K7, Canada.

Journal of translational medicine

|October 1, 2025

概括

PREFFECT是一个新的计算框架,可以改进对已降解的甲固定嵌入 (FFPE) 样品的RNA测序分析. 它准确地归纳缺少的数据并调整批量效应,增强临床研究的下游分析.

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:

嵌入式甲固化 (FFPE) 样本显示核酸降解,使高通量测序复杂化.
FFPE RNA测序 (fRNA-seq) 数据带来了像转录丢失和高方差这样的挑战,阻碍了下游分析.

研究的目的:

介绍PREFFECT,用于分析fRNA-seq数据的概率框架.
解决fRNA-seq数据集数据质量和分析方面的挑战.

主要方法:

PREFFECT采用生成模型来适应表达数分布,并根据技术和生物变量进行调整.
它利用匹配的组织配置文件进行稳定和归算,并利用样本-样本相邻网络与图表注意力机制.

主要成果:

负二项分布被确定为最适合fRNA-seq转录数的分布.
在使用相邻网络和多个组织时,PREFFECT准确地赋值缺失值,调整批量效应,并增强样本聚类.

结论:

与通用散装RNA-seq工具相比,PREFFECT提供了改进和特定的模型匹配,特别是与匹配的配置文件.
该框架的转换数据与现有工具兼容,支持临床生物标志物发现和诊断.

关键词:

嵌入式固定式甲嵌入式固定式甲.生成式建模生成式建模图表注意力网络的图表.通过RNA测序来测序RNA序列.

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