infercnv包也包含了画图函数plot_cnv: library(RColorBrewer) infercnv::plot_cnv(infercnv_obj, #上两步得到的infercnv对象 plot_chr_scale = T, #画染色体全长,默认只画出(分析用到的)基因 output_filename = "better_plot",output_format = "pdf", #保存为pdf文件 custom_color_pal = color.palette(c...
options(stringsAsFactors =F)library(phylogram)library(gridExtra)library(grid)require(dendextend)require(ggthemes)library(tidyverse)library(Seurat)library(infercnv)library(miscTools)# Import inferCNV dendrograminfercnv.dend <- read.dendrogram(file ="plot_out/inferCNV_output2/infercnv.observations_dendrogram.tx...
infercnv::plot_cnv(infercnv_obj, #上两步得到的infercnv对象 plot_chr_scale = T, #画染色体全长,默认只画出(分析用到的)基因 output_filename = "better_plot",output_format = "pdf", #保存为pdf文件 custom_color_pal = color.palette(c("#8DD3C7","white","#BC80BD"), c(2, 2))) #改...
(infercnv.dend)))%>%plot(main="inferCNV dendrogram")%>%colored_bars(colors=as.data.frame(the_bars),dend=infercnv.dend,sort_by_labels_order=FALSE,add=T,y_scale=10,y_shift=0)dev.off()infercnv.labels=as.data.frame(infercnv.labels)groupFiles='data/ep-infercnv.groupFiles.txt'meta=read....
infercnv.dend<-read.dendrogram(file="plot_out/inferCNV_output2/infercnv.observations_dendrogram.txt")# Cut tree infercnv.labels<-cutree(infercnv.dend,k=6,order_clusters_as_data=FALSE)table(infercnv.labels)# Color labels the_bars<-as.data.frame(tableau_color_pal("Tableau 20")(20)[infercnv.la...
infercnv.dend<-read.dendrogram(file="plot_out/inferCNV_output2/infercnv.observations_dendrogram.txt")# Cut tree infercnv.labels<-cutree(infercnv.dend,k=6,order_clusters_as_data=FALSE)table(infercnv.labels)# Color labels the_bars<-as.data.frame(tableau_color_pal("Tableau 20")(20)[infercnv.la...
infercnv.dend %>% set("labels",rep("", nobs(infercnv.dend)) ) %>% plot(main="inferCNV dendrogram") %>% colored_bars(colors = as.data.frame(the_bars), dend = infercnv.dend, sort_by_labels_order =FALSE, add =T, y_scale=100, y_shift =0) ...
hspike_aggregate_normals =FALSE, no_plot =FALSE, no_prelim_plot =FALSE, output_format ="png", useRaster =TRUE, up_to_step =100) 多到让人头皮发麻! 其中文献运行infercnv::run的时候,下面两个参数,都是默认值: HMM参数 when set to True, runs HMM to predict CNV level (default: FALSE) ...
#新建,原来没有这个文件夹>## 文献的代码:#14:58开始>start_time<-Sys.time()>## 文献的代码:#14:58开始>start_time<-Sys.time()>infercnv_obj2=infercnv::run(infercnv_obj,+cutoff=0.1,# cutoff=1 works well for Smart-seq2, and cutoff=0.1 works well for 10x Genomics+out_dir='plot_out/'...
NOC2L chr1 879584894689 MIR200A chr1 11032431103332 实例操作 我们利用infercnv软件里面自带的例子做分析。主要步骤只有两步,如下 创建infercnv的对象 library(infercnv) # Create the InferCNV Object infercnv_obj = CreateInfercnvObject(raw_counts_matrix = system.file("extdata", "oligodendroglioma_expression_dow...