1

我有一个相当大的 data.frame，我必须对其进行一些处理。目前的结构是：

V1   V2 V3 V4 V5         V6        V7         V8         ...   Vn         Vn+1
chr1  1 A  T  sample_1   value_1   sample_2   value_4   ...   sample_n   value_7 
chr1 40 T  C  sample_1   value_2   sample_2   value_5   ...   sample_n   value_8
chr1 60 A  T  sample_1   value_3   sample_2   value_6   ...   sample_n   value_9
.
.
.
chrX 160 A  T  sample_1   value_x   sample_2   value_y   ...  sample_n value_ni

例如对于 data_frame：

df <- structure(list(V1 = c(10L, 10L, 10L, 10L, 10L, 10L), V2 = c(3387501L, 
4174142L, 6419754L, 6419765L, 6419897L, 6419912L), V3 = c("T", 
"A", "C", "T", "G", "A"), V4 = c("A", 
"T", "A", "A", "C", "G"), V5 = c("LP2000748-DNA_H02", 
"LP2000748-DNA_H02", "LP2000748-DNA_H02", "LP2000748-DNA_H02", 
"LP2000748-DNA_H02", "LP2000748-DNA_H02"), V6 = c("0/0", "0/0", 
"1/1", "0/0", "0/0", "0/0"), V7 = c("LP2000748-DNA_A03", "LP2000748-DNA_A03", 
"LP2000748-DNA_A03", "LP2000748-DNA_A03", "LP2000748-DNA_A03", 
"LP2000748-DNA_A03"), V8 = c("0/0", "0/0", "1/1", "0/1", "0/0", 
"0/0"), V9 = c("LP2000795-DNA_B01", "LP2000795-DNA_B01", "LP2000795-DNA_B01", 
"LP2000795-DNA_B01", "LP2000795-DNA_B01", "LP2000795-DNA_B01"
), V10 = c("0/0", "0/0", "1/1", "0/0", "0/0", "0/0")), row.names = c(NA, 
-6L), class = c("data.table", "data.frame"))

我最终想要的是这样的表格：

V1   V2 V3 V4 sample_1   sample_2   ...   sample_n    
chr1  1 A  T   value_1    value_4   ...    value_7 
chr1 40 T  C   value_2    value_5   ...    value_8
chr1 60 A  T   value_3    value_6   ...    value_9
.
.
.
chrX 160 A  T   value_x    value_y   ...  value_ni

到目前为止，我在 R 中尝试过的是：

samples_data <- seq(from = 5, to = dim(df)[2],by=2) variable_data <- samples_data + 1

new_df <- reshape2::dcast(df, V1 + V2 + V3 ~ colnames(df)[samples_data], value.var= colnames(df)[variable_data])

但我收到此错误消息：

  recursive indexing failed at level 2
In addition: Warning message:
In if (!(value.var %in% names(data))) { :
  the condition has length > 1 and only the first element will be used

有没有人对如何解决这个问题或如何重塑 df 有任何建议？

谢谢！

4

1 回答 1

0

您可能需要取消嵌套数据，然后使用reshape. 要取消嵌套，您可以使用Map生成一个列表，选择前四个 ID 列，然后从其余列中选择模式 5,6；7,8; 9,10。rbind结果和reshape。

cseq <- 5:ncol(df)
tmp <- do.call(rbind, Map(function(x, y) setNames(df[c(1:4, x:y)], 
                                                  c(names(df)[1:4], c("sample", "value"))), 
                   cseq[cseq %% 2 != 0], cseq[cseq %% 2 == 0]))
res <- reshape(tmp, idvar=1:4, timevar="sample", v.names="value", direction="wide")
res
#   V1      V2 V3 V4 value.LP2000748-DNA_H02 value.LP2000748-DNA_A03 value.LP2000795-DNA_B01
# 1 10 3387501  T  A                     0/0                     0/0                     0/0
# 2 10 4174142  A  T                     0/0                     0/0                     0/0
# 3 10 6419754  C  A                     1/1                     1/1                     1/1
# 4 10 6419765  T  A                     0/0                     0/1                     0/0
# 5 10 6419897  G  C                     0/0                     0/0                     0/0
# 6 10 6419912  A  G                     0/0                     0/0                     0/0
于 2020-03-23T13:17:26.477 回答