写在开头
今天我们分享的任务是来自：生物学功能注释三板斧。 本次任务我计划分为四个部分来写，今天写第二部分。
2.PROGENy--单细胞通路活性评分
3.DoRothEA--转录组转录因子评分
4.PROGENy--转录组通路活性评分
正文部分
相较于其他通路活性评估算法，使用 PROGENy 能够构建通路核心基因集及基因的贡献权重，对通路活性评估更加准确有效；同时 PROGENy 能够精确定位癌症或病变中发生关键变化的通路节点，可以为生物学研究提供更加准确可靠的结果。
作者主要着眼于癌症中10种信号通路，如下c
加载R包和数据
library(dplyr)library(tibble)library(tidyr)library(patchwork)library(ggplot2)library(pheatmap)library(Seurat)library(progeny)library(Seurat)library(decoupleR)getwd()dir.create("~/gzh/20240414_progeny_通路活性分析")setwd("~/gzh/20240414_progeny_通路活性分析")getwd()load("~/gzh/pbmc3k_final_v4.rds")table(Idents(pbmc))
pbmc单细胞数据：
计算通路活性
# We create a data frame with the specification of the cells that belong to## each cluster to match with the Progeny scores.CellsClusters <- data.frame(Cell = names(Idents(pbmc)),CellType = as.character(Idents(pbmc)),stringsAsFactors = FALSE)head(CellsClusters)DimPlot(pbmc, reduction = "umap", label = TRUE, pt.size = 0.5) + NoLegend()2 #2-------## We compute the Progeny activity scores and add them to our Seurat object## as a new assay called Progeny.pbmc <- progeny(pbmc, scale=FALSE, organism="Human", top=500, perm=1, return_assay = TRUE) #"Human" Mousepbmc@assays$progenypbmc@assays$progeny %>%dim()pbmc@assays$progeny@data[,1:19]# Assay data with 14 features for 2638 cells # First 10 features:# Androgen, EGFR, Estrogen, Hypoxia, JAK-STAT, MAPK, NFkB, p53, PI3K, TGFb
计算得到通路活性矩阵：
后续的可视化分析又是各显神通了！
对通路活性矩阵进行可视化一
library(viridis)progeny_hmap = pheatmap(t(summarized_progeny_scores_df),fontsize=12,fontsize_row = 10, color=myColor,breaks = progenyBreaks, main = "PROGENy",angle_col = 45, treeheight_col = 0, border_color = NA)
progeny_hmap = pheatmap(t(summarized_progeny_scores_df),fontsize=12,fontsize_row = 10, color=turbo(90),main = "PROGENy",angle_col =90, treeheight_col = 0, border_color = NA)
可视化二
library(viridis)DefaultAssay(pbmc) <- 'progeny'p1= FeaturePlot(pbmc,features = "NFkB", coord.fixed = T,label = TRUE,order = T, cols = viridis(10))p2=FeaturePlot(pbmc,features = "MAPK", coord.fixed = T, order = T, cols = viridis::turbo(10))p1|p2
参考：https://saezlab.github.io/progeny/articles/ProgenySingleCell.htmlhttps://www.jianshu.com/p/4058050d546ehttps://saezlab.github.io/progeny/articles/progeny.html
