数据帧上的扩展函数（R中有重复项）

我正试图以一种有效的方式将复制从数据集中的结果中分离出来。我以这些数据为例：

x <- data.frame(sample = c("AA", "AA", "BB", "BB", "CC", "CC"),
                Gene = c("HSA-let1","HSA-let1","HSA-let1","HSA-let1","HSA-let1","HSA-let1"),
                Cq = c(14.55, 14.45, 13.55, 13.45, 16.55, 16.45))

我得到了重复的标识符错误。我尝试了下面的修复代码，它在一个列中给出了两个值，用“，”分隔。这几乎成功了，但我希望他们分开：

x_test <- dcast(setDT(x), Gene ~ sample, value.var = 'Cq',
                fun.aggregate = function(x) toString(unique(x)))

---

您可以更改

sample

列：

library(data.table)

setDT(x)[, sample := paste(sample, ifelse(!duplicated(sample), '1', '2'), sep = '_')]
dcast(x, ...~sample, value.var = 'Cq')
#        Gene  AA_1  AA_2  BB_1  BB_2  CC_1  CC_2
# 1: HSA-let1 14.55 14.45 13.55 13.45 16.55 16.45

注：

spread

应称为

spread（x，sample，Cq）

编辑 如果有不同数量的重复值（不总是2），可以执行以下操作：

x <- setDT(x)[order(sample),]
x[, sample := paste(sample, unlist(lapply(table(x$sample), function(x) 1:x)), sep = '_')]
dcast(x, ...~sample, value.var = 'Cq')

x你可以试试这个

library(dplyr)
x %>% group_by(Gene) %>%
  mutate(sample = paste(sample, seq(n()), sep = "_")) %>%
  spread(sample, Cq)

使样品独特，然后传播：

x %>% 
  group_by(sample) %>% 
  mutate(rn = row_number()) %>% 
  ungroup() %>% 
  mutate(sample = paste(sample, rn, sep = "_")) %>% 
  select(-rn) %>% 
  spread(key = sample, value = Cq)

# # A tibble: 1 x 7
#     Gene      AA_1  AA_2  BB_1  BB_2  CC_1  CC_2
#     <fct>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#   1 HSA-let1  14.6  14.4  13.6  13.4  16.6  16.4

x%>%
分组依据（样本）%>%
变异（rn=行数（））%>%
解组（）%>%
变异（样本=粘贴（样本，rn，sep=“”））%>%
选择（-rn）%>%
排列（键=样本，值=Cq）
##A tible:1 x 7
#基因AA_1 AA_2 BB_1 BB_2 CC_1 CC_2
#              
#1 HSA-let1 14.6 14.4 13.6 13.4 16.6 16.4

x <- setDT(x)[order(sample),]
x[, sample := paste(sample, unlist(lapply(table(x$sample), function(x) 1:x)), sep = '_')]
dcast(x, ...~sample, value.var = 'Cq')

library(dplyr)
x %>% group_by(Gene) %>%
  mutate(sample = paste(sample, seq(n()), sep = "_")) %>%
  spread(sample, Cq)

x %>% 
  group_by(sample) %>% 
  mutate(rn = row_number()) %>% 
  ungroup() %>% 
  mutate(sample = paste(sample, rn, sep = "_")) %>% 
  select(-rn) %>% 
  spread(key = sample, value = Cq)

# # A tibble: 1 x 7
#     Gene      AA_1  AA_2  BB_1  BB_2  CC_1  CC_2
#     <fct>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#   1 HSA-let1  14.6  14.4  13.6  13.4  16.6  16.4