福建省住房城乡建设厅网站,广东省自然资源厅陈光荣,电子产品展示网站模板,网站建设的关键技术前提#xff1a;接着上述R脚本输出的seed结果来选择应该使用哪个seed比较合理#xff0c;上个R脚本名字#xff1a; “5utr_计算ABD中Ge1和Lt1的个数和均值以及按照TE个数小的进行随机100次抽样.R” 1.输入数据#xff1a;“5utr-5d做ABD中有RG4和没有RG4的TE之间的T检验.c…前提接着上述R脚本输出的seed结果来选择应该使用哪个seed比较合理上个R脚本名字 “5utr_计算ABD中Ge1和Lt1的个数和均值以及按照TE个数小的进行随机100次抽样.R” 1.输入数据“5utr-5d做ABD中有RG4和没有RG4的TE之间的T检验.csv”
2.代码“5utr_5d_ABD中有RG4和无RG4的TE之间的T检验函数保存符合要求的seed保存符合要求的数据框绘制boxplot.R”
setwd(E:\\R\\Rscripts\\5UTR_extended_TE)
# 载入必要的库
library(tidyverse)
library(dplyr)
library(openxlsx)# 读取数据
data - read.csv(5utr-5d做ABD中有RG4和没有RG4的TE之间的T检验.csv, na.strings #N/A)# 将所有的NA值转换为0
data - data %% mutate_all(~ifelse(is.na(.), 0, .))############################################################
# 调整后的process_scores函数1,适用于le1的个数小于ge1的个数且ave-le1大于ave-ge1的情况
############################################################process_scores - function(df, score_name, TE_name) {successful_seeds - list() # 初始化一个列表来保存成功的seed值combined_samples_list - list() # 新增初始化一个列表来保存符合条件的组合数据框for (seed_val in 1) {set.seed(seed_val)ge1 - df %% filter(!!sym(score_name) 1) %% select(!!sym(TE_name)) %% mutate(Source ge1)le1 - df %% filter(!!sym(score_name) 1) %% select(!!sym(TE_name)) %% mutate(Source sample_le1)sample_le1 - sample_n(le1, nrow(ge1)) # 取单一样本进行比较t_test - t.test(ge1[[1]], sample_le1[[1]])mean1 - mean(ge1[[1]])mean2 - mean(sample_le1[[1]])if (mean2 mean1 t_test$p.value 0.09) {successful_seeds[[paste0(seed_val, _, score_name)]] - list(seed seed_val,mean1 mean1,mean2 mean2,pvalue t_test$p.value)# 新增将符合条件的ge1和sample_le1合并到一个数据框中并保存到列表中combined_samples - bind_rows(ge1, sample_le1)combined_samples_list[[paste0(seed_val, _, score_name)]] - combined_samples}}# 将成功的seeds信息转换为数据框if (length(successful_seeds) 0) {successful_seeds_df - bind_rows(successful_seeds, .id seed_score) %% mutate(Comparison seed_score)} else {successful_seeds_df - tibble(Comparison character(), mean1 numeric(), mean2 numeric(), pvalue numeric())}# 新增将combined_samples_list中的数据框合并或以其他形式输出combined_samples_output - if (length(combined_samples_list) 0) {# 例如这里我们简单地将所有符合条件的数据框合并bind_rows(combined_samples_list)} else {# 如果没有符合条件的则返回空数据框tibble()}return(list(successful_seeds successful_seeds_df, combined_samples combined_samples_output))
}# 对AScore5d进行处理示例
results_AScore5d - process_scores(data, AScore5d, ATe5d)
results_BScore5d - process_scores(data, BScore5d, BTe5d)
results_DScore5d - process_scores(data, DScore5d, DTe5d)
# 打印出符合条件的successful_seeds结果进行检查
bind_results_AScore5d_successful_seeds-rbind(results_AScore5d$successful_seeds,results_BScore5d$successful_seeds,results_DScore5d$successful_seeds)
write.xlsx(bind_results_AScore5d_successful_seeds, file 5utr_bind_results_ABDScore5d_successful_seeds_seed1.xlsx)# 将符合条件的组合数据框写入文件
write.table(results_AScore5d$combined_samples, combined_samples_seed1_5utr5dAScored.csv, quote FALSE, row.names FALSE, sep ,)
write.table(results_BScore5d$combined_samples, combined_samples_seed1_5utr5dBScored.csv, quote FALSE, row.names FALSE, sep ,)
write.table(results_DScore5d$combined_samples, combined_samples_seed1_5utr5dDScored.csv, quote FALSE, row.names FALSE, sep ,)####################################################################
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#接着上面的结果绘制boxplot
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library(tidyverse)
library(ggplot2)
library(patchwork)results_AScore5d$combined_samples$Source-factor(results_AScore5d$combined_samples$Source,levelsc(ge1,sample_le1),labelsc(A with rG4,A without rG4),orderedTRUE)
p1-ggplot(results_AScore5d$combined_samples, aes(xSource,yATe5d,fillSource))#根据Type进行填充fillTypestat_boxplot(geom errorbar,width0.1) #添加误差线geom_boxplot(outlier.size -1,width0.25)theme_classic()#背景设置为白色scale_fill_manual(values c( #8DD3C7, #FC8D62))labs(yTE)scale_y_continuous(limits c(0,5),breaksseq(0,5,1))theme(strip.background element_rect(colourblack, fill#FFFFFF),plot.titleelement_text (hjust 0.5,vjust 1,lineheight1,colorblack),panel.backgroundelement_rect(fillwhite,colourblack,linewidth 0.5),axis.title.yelement_text(size25,faceplain,colorblack),axis.title.xelement_blank(),axis.text element_text(size20,faceplain,colorblack),#axis.tex用来调整描述x轴的文本比如图中的conserved等panel.border element_blank(),panel.grid.major element_blank(),panel.grid.minor element_blank(),axis.ticks.xelement_line(colourblack),axis.ticks.length.xgrid::unit(0.2, cm))guides(fillnone)results_BScore5d$combined_samples$Source-factor(results_BScore5d$combined_samples$Source,levelsc(ge1,sample_le1),labelsc(B with rG4,B without rG4),orderedTRUE)
p2-ggplot(results_BScore5d$combined_samples, aes(xSource,yBTe5d,fillSource))#根据Type进行填充fillTypestat_boxplot(geom errorbar,width0.1) #添加误差线geom_boxplot(outlier.size -1,width0.25)theme_classic()#背景设置为白色scale_fill_manual(values c( #8DD3C7, #FC8D62))labs(yTE)scale_y_continuous(limits c(0,5),breaksseq(0,5,1))theme(strip.background element_rect(colourblack, fill#FFFFFF),plot.titleelement_text (hjust 0.5,vjust 1,lineheight1,colorblack),panel.backgroundelement_rect(fillwhite,colourblack,linewidth 0.5),axis.title.yelement_text(size25,faceplain,colorblack),axis.title.xelement_blank(),axis.text element_text(size20,faceplain,colorblack),#axis.tex用来调整描述x轴的文本比如图中的conserved等panel.border element_blank(),panel.grid.major element_blank(),panel.grid.minor element_blank(),axis.ticks.xelement_line(colourblack),axis.ticks.length.xgrid::unit(0.2, cm))guides(fillnone)results_DScore5d$combined_samples$Source-factor(results_DScore5d$combined_samples$Source,levelsc(ge1,sample_le1),labelsc(D with rG4,D without rG4),orderedTRUE)
p3-ggplot(results_DScore5d$combined_samples, aes(xSource,yDTe5d,fillSource))#根据Type进行填充fillTypestat_boxplot(geom errorbar,width0.1) #添加误差线geom_boxplot(outlier.size -1,width0.25)theme_classic()#背景设置为白色scale_fill_manual(values c( #8DD3C7, #FC8D62))labs(yTE)scale_y_continuous(limits c(0,5),breaksseq(0,5,1))theme(strip.background element_rect(colourblack, fill#FFFFFF),plot.titleelement_text (hjust 0.5,vjust 1,lineheight1,colorblack),panel.backgroundelement_rect(fillwhite,colourblack,linewidth 0.5),axis.title.yelement_text(size25,faceplain,colorblack),axis.title.xelement_blank(),axis.text element_text(size20,faceplain,colorblack),#axis.tex用来调整描述x轴的文本比如图中的conserved等panel.border element_blank(),panel.grid.major element_blank(),panel.grid.minor element_blank(),axis.ticks.xelement_line(colourblack),axis.ticks.length.xgrid::unit(0.2, cm))guides(fillnone)
p4-p1p2p3plot_layout(widths c(1,1,1))
ggsave(boxplot-5utr-5d做ABD中有RG4和没有RG4的TE之间的T检验.pdf,plotp4,width24,height10)3.输出数据“5utr_bind_results_ABDScore5d_successful_seeds_seed1.xlsx”
4.输出boxplot“boxplot-5utr-5d做ABD中有RG4和没有RG4的TE之间的T检验.pdf”
