讀CIBERSORT免疫浸潤的代碼實現、cibersoft使用SVM算法實現去卷積有感，知識連貫性即系統性最終決定你能否得到自己想要的結果。
cybersort
Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015 May;12(5):453-7. doi: 10.1038/nmeth.3337. Epub 2015 Mar 30. PMID: 25822800; PMCID: PMC4739640.
二、輸入數據類型
Importantly, all expression data should be non-negative, devoid of missing values, and represented in non-log linear space.
For Affymetrix microarrays, a custom chip definition file (CDF) is recommended (see Subheading 3.2.2) and should be normalized with MAS5 or RMA.
Illumina Beadchip and single color Agilent arrays should be processed as described in the limma package.
Standard RNA-Seq expression quantification metrics, such as frag- ments per kilobase per million (FPKM) and transcripts per kilobase million (TPM), are suitable for use with CIBERSORT. –《Profiling Tumor Infiltrating Immune Cells with CIBERSORT》
首先，所有的數據要求非負，無缺失值，未經過log轉化
1、Affymetrix microarrays芯片數據要求 MAS5 or RMA標準化
2、Illumina Beadchip 需要經limma package處理
3、RNA-seq數據可以使用FPKM和TPM
TCGA中肝癌數據進行演示：
rm(list = ls())
library(tidyverse)
library(ggplot2)
library(stringr)
load("../3.DEGs/tpm_exp.Rdata")
load("../3.DEGs/DEG_limma.Rdata")
exp <- 2^tpm_exp-1
exp <- exp[,str_sub(colnames(exp),1,15)%in%group$Sample.ID]
exp <- exp[,match(group$Sample.ID,str_sub(colnames(exp),1,15))] %>%
rownames_to_column()
write.table(exp,file = "exp.txt",sep = "\t",row.names = F,quote = F)
我直接在UCSC中下載了FPKM的數據，由于我之前已經轉化未log2(TPM+1)，這里為了滿足要求，我直接轉化未TPM，將行名轉換為列，保存未txt文件備用。
rm(DEG_limma,exp,tpm_exp)
if(F){
library(e1071)
source("CIBERSORT.R")
TME.results = CIBERSORT("LM22.txt",
"exp.txt" ,
perm = 1,
QN = T)
save(TME.results,file = "ciber.Rdata")
}
load("ciber.Rdata")
我本想先使用了374個樣本運行代碼，再挑選我需要的樣本免疫細胞浸潤情況，無奈運行時間有點長，讓我誤以為自己電腦壞了/////////所以，這里我挑選了73個樣本直接運行，速度還可以，不到一分鐘搞定，得到矩陣。
三、數據展示
1、免疫細胞豐度熱圖
#--熱圖---------------------------------------------------------------------------------------------
re <- TME.results[,-(23:25)]
library(pheatmap)
k <- apply(re,2,function(x) {sum(x == 0) < nrow(TME.results)/2})
table(k)
## k
## FALSE TRUE
## 9 13
re2 <- as.data.frame(t(re[,k]))
an = data.frame(group = group$Disease.Free.Status,
row.names = colnames(re2))
pheatmap(re2,scale = "row",
show_colnames = F,cluster_cols = F,
annotation_col = an,breaks = seq(-2,2,length.out = 50),
color = colorRampPalette(c("navy", "white", "firebrick3"))(50))
2、直方圖
#---barplot---------------------------------------------------------------------------------------------
library(RColorBrewer)
mypalette <- colorRampPalette(brewer.pal(8,"Set1"))
dat <- re %>% as.data.frame() %>%
rownames_to_column("Sample") %>%
gather(key = Cell_type,value = Proportion,-Sample)
ggplot(dat,aes(Sample,Proportion,fill = Cell_type)) +
geom_bar(stat = "identity") +
labs(fill = "Cell Type",x = "",y = "Estiamted Proportion") +
theme_bw() +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
legend.position = "bottom") +
scale_y_continuous(expand = c(0.01,0)) +
scale_fill_manual(values = mypalette(22))
3、 箱線圖
#------------------------------------------------------------------------
a = dat %>%
group_by(Cell_type) %>%
summarise(m = median(Proportion)) %>%
arrange(desc(m)) %>%
pull(Cell_type)
dat$Cell_type = factor(dat$Cell_type,levels = a)
ggplot(dat,aes(Cell_type,Proportion,fill = Cell_type)) +
geom_boxplot(outlier.shape = 21,color = "black") +
theme_bw() +
labs(x = "Cell Type", y = "Estimated Proportion") +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
legend.position = "bottom") +
scale_fill_manual(values = mypalette(22))
#----------------------------------------------------------------------------
dat$Group = factor(rep(group$Disease.Free.Status,times=22),levels = c(0,1))
library(ggpubr)
ggplot(dat,aes(Cell_type,Proportion,fill = Group)) +
geom_boxplot(outlier.shape = 21,color = "black") +
theme_bw() +
labs(x = "Cell Type", y = "Estimated Proportion") +
theme(legend.position = "top") +
theme(axis.text.x = element_text(angle=60,hjust =1))+
scale_fill_manual(values = mypalette(22)[c(6,1)])+
stat_compare_means(aes(group = Group,label = ..p.signif..),method = "t.test")
