pool = 1:10 for(fish in pool){ print(fish) }
通过循环操作读取文件并进行数据的处理
files = c('DEG1.xls', 'DEG2.xls', 'DEG3.xls', 'DEG4.xls') n = 1 for(file in files){ print(paste0('DEG unfiltered file is ', file)) # 1 reading DEG unfiltered file df = read.delim(file, header = T, sep = '\t') # 2 filtering different expressed genes df$logFC = log2(df$FC) deg = subset(df, abs(logFC) > 1 & pval < 0.05) # 3 reading TF annotation file TF = read.delim('Homo_sapiens_TF.txt', header = T, sep = '\t') # 4 annotate DEGs with TF family information deg_TF_all = merge(deg, TF, by.x = 'id', by.y = 'Symbol', all.x = T) # 5 output annotated DEGs outfile_name = paste0('deg_TF_', n, '.xls') write.table(deg_TF_all, outfile_name, col.names = T, row.names = F, sep = '\t', quote = F) n = n + 1 }
判断
a = 2 b = 3 c = 1 if(a > b){ print('a > b') } if(a > b){ print('a > b') } else { print('a <= b') } if(a > b){ print('a > b') } else if(a > c){ print('a > c') } else { print('a <= b and a <= c') }
基本语法和java与C语言有点类似，思想和Python相符合
批量处理4个文件：差异筛选+TF注释
如果已经加载TF数据库，则不再读取
files = c('DEG1.xls', 'DEG2.xls', 'DEG3.xls', 'DEG4.xls') n = 1 for(file in files){ print(paste0('Processing file is ', file)) # 1 reading DEG unfiltered file df = read.delim(file, header = T, sep = '\t') # 2 filtering different expressed genes df$logFC = log2(df$FC) deg = subset(df, abs(logFC) > 1 & pval < 0.05) if(exists('TF')){ print('TF database has already existed') } else { # 3 reading TF annotation file TF = read.delim('Homo_sapiens_TF.txt', header = T, sep = '\t') } # 4 annotate DEGs with TF family information deg_TF_all = merge(deg, TF, by.x = 'id', by.y = 'Symbol', all.x = T) # 5 output annotated DEGs outfile_name = paste0('deg_TF_', n, '.xls') write.table(deg_TF_all, outfile_name, col.names = T, row.names = F, sep = '\t', quote = F) n = n + 1 }
对于基本的循环判断其实和其他的编译语言差不多
