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一篇单细胞和WGCNA结合的文献解读-1

2020-06-01  本文已影响0人  小梦游仙境

文章题目

Single Cell Gene Co-Expression Network Reveals FECH/CROT Signature as a Prognostic Marker

背景知识

AR(Androgen receptor,雄激素受体)活性的增加驱动晚期前列腺癌的治疗耐药,深入剖析AR调控网络的机制至关重要。GCN(co-expression network)有助于成功识别AR变量驱动的基因模块,但是由于GCN的高度稀疏性和维数高,为所有被检测基因构建的GCN太大而无法解释。而加权相关网络分析(WGCNA)利用层次聚类方法识别基因簇,并能提取潜在表型的有意义的生物信息。近期研究表明LNCaP细胞对雄激素剥夺治疗反应不一。现已发现雄激素剥夺治疗的耐药亚群,其特征是细胞周期活动增强。因此,本研究旨在从单细胞的角度找出AR调控的关键生物学过程及其雄激素调控基因。

==androgen(R1881)==,也被称为甲基三烯醇,是一种合成的雄激素。它是AR激动剂。

biomodal:双峰性表达,描述如下图

image-20200601113642215

BI value:BI index,用来代表 biomodal expression的extent,The bimodality index (BI) is used to distribution of marker genes (AR, KLK3, and TMPRSS2) in single cells; Genes with BI > 1.2 are regarded as bimodally expressed genes

材料方法

数据:We downloaded the processed expression (RPKM) profiles of LNCaP cells generated by single cell RNA-seq from GEO (accession ID: GSE99795). The dataset contains 144 LNCaP cells from 0 h untreated, 12 h untreated and 12 h R1881 treated conditions. There are 48 cells under each condition.

Bimodality expression was performed using the ==R package, SIBER== . First, a normal mixture model (‘NL’) was specified on the log2 transformed RPKM expression values to fit the gene expression distribution into a two component mixture model (component 1 and 2). Next the average values (mu1 and mu2) were calculated. Other parameters were also obtained including variance values (sigma1, sigma2) and corresponding proportion of the component 1 and 2 (pi1 and pi2).

结果

结果1.我们尝试用双峰表达模式来表征细胞的异质性。

image-20200601112841618 image-20200601114836790

结果2.WGCNA

image-20200601113020409

结果3.确定由AR调控的模块

image-20200601113404534

结果4. 由AR受体调控的 Biological Functions of Modules

==应用的包是RobustRankaAggreg==

image-20200601114617483 image-20200601115533800

结果5.FECH and CROT在病人中的表达

image-20200601121303350 image-20200601121310723

结果6.FECH/CROT 可以作为由AR调控的预后因子 image-20200601121913343

image-20200601121943767 image-20200601122352176 image-20200601122434810
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