通过按字母顺序仅对一行中的一些字段进行排序来重塑 R 中的数据框

Posted 2023-03-27

【中文标题】通过按字母顺序仅对一行中的一些字段进行排序来重塑 R 中的数据框

【英文标题】：Reshaping a dataframe in R by sorting just some fields in a row alphabetically

【发布时间】：2022-01-05 14:50:48

【问题描述】：

我在 RStudio 中有一些大型数据框，它们具有这种结构：

Original data structure

structure(list(CHROM = c("scaffold1000|size223437", "scaffold1000|size223437", 
"scaffold1000|size223437", "scaffold1000|size223437"), POS = c(666, 
1332, 3445, 4336), REF = c("A", "TA", "CTTGA", "GCTA"), RO = c(20, 
14, 9, 25), ALT_1 = c("GAT", "TGC", "AGC", "T"), ALT_2 = c("CAG", 
"TGA", "CGC", NA), ALT_3 = c("G", NA, "TGA", NA), ALT_4 = c("AGT", 
NA, NA, NA), AO_1 = c(13, 4, 67, 120), AO_2 = c(12, 5, 34, NA
), AO_3 = c(6, NA, 18, NA), AO_4 = c(101, NA, NA, NA), AOF_1 = c(8.55263157894737, 
17.3913043478261, 52.34375, 82.7586206896552), AOF_2 = c(7.89473684210526, 
21.7391304347826, 26.5625, NA), AOF_3 = c(3.94736842105263, NA, 
14.0625, NA), AOF_4 = c(66.4473684210526, NA, NA, NA)), class = "data.frame", row.names = c(NA, 
-4L))

但为了进行分析，我需要它看起来像这样：

Desired output

 structure(list(CHROM = c("scaffold1000|size223437", "scaffold1000|size223437", 
    "scaffold1000|size223437", "scaffold1000|size223437"), POS = c(666, 
    1332, 3445, 4336), REF = c("A", "TA", "CTTGA", "GCTA"), RO = c(20, 
    14, 9, 25), ALT_1 = c("AGT", "TGA", "AGC", "T"), ALT_2 = c("CAG", 
    "TGC", "CGC", NA), ALT_3 = c("G", NA, "TGA", NA), ALT_4 = c("GAT", 
    NA, NA, NA), AO_1 = c(101, 5, 67, 120), AO_2 = c(12, 4, 34, NA
    ), AO_3 = c(6, NA, 18, NA), AO_4 = c(13, NA, NA, NA), AOF_1 = c(66.4473684210526, 
    21.7391304347826, 52.34375, 82.7586206896552), AOF_2 = c(7.89473684210526, 
    17.3913043478261, 26.5625, NA), AOF_3 = c(3.94736842105263, NA, 
    14.0625, NA), AOF_4 = c(8.55263157894737, NA, NA, NA)), class = "data.frame", row.names = c(NA, 
    -4L))

所以我想做的是以某种方式重新排列一行的内容，列 ALT_1、ALT_2、ALT_3、ALT_4 是按字母顺序排序的，但同时我还需要重新排列相应的列AO 和 AOF，使值仍然匹配。 （AO_1 的值仍应与 ALT_1 中的序列匹配。 所以如果 ALT_1 在排序后的数据帧中变成 ALT_2，AO_1 也应该变成 AO_2)

到目前为止我尝试过的，但没有奏效：

将 ALT_1、AO_1、AOF_1 的值全部粘贴到一个字段中，所以我将它们放在一起

  if (is.na(X[i,6]) == FALSE) 
    X[i,6] <- paste(X[i,6],X[i,10],X[i,14],sep=" ")
  

然后我想将每一行提取为向量以对值进行排序并将其放回数据框中，但我没有设法做到这一点。

所以问题是我如何订购数据框以获得所需的输出？ （我需要将此应用于 32 个数据帧，每个数据帧具有 >100.000 个值）

【问题讨论】：

请不要将数据共享为图像，请改用dput()。谢谢。

【参考方案1】：

这是data.table 方法

library(data.table)
# Set to data.table format
setDT(mydata)
# Melt to long format
DT.melt <- melt(mydata, measure.vars = patterns(ALT = "^ALT_", AO = "^AO_", AOF = "^AOF_"))
# order by groups, na's at the end
setorderv(DT.melt, cols = c("CHROM", "POS",  "ALT"), na.last = TRUE)
# cast to wide again, use rowid() for numbering
dcast(DT.melt, CHROM + POS + REF + RO ~ rowid(REF), value.var = list("ALT", "AO", "AOF"))
#                      CHROM  POS   REF RO ALT_1 ALT_2 ALT_3 ALT_4 AO_1 AO_2 AO_3 AO_4    AOF_1     AOF_2     AOF_3    AOF_4
# 1: scaffold1000|size223437  666     A 20   AGT   CAG     G   GAT  101   12    6   13 66.44737  7.894737  3.947368 8.552632
# 2: scaffold1000|size223437 1332    TA 14   TGA   TGC  <NA>  <NA>    5    4   NA   NA 21.73913 17.391304        NA       NA
# 3: scaffold1000|size223437 3445 CTTGA  9   AGC   CGC   TGA  <NA>   67   34   18   NA 52.34375 26.562500 14.062500       NA
# 4: scaffold1000|size223437 4336  GCTA 25     T  <NA>  <NA>  <NA>  120   NA   NA   NA 82.75862        NA        NA       NA

【讨论】：

非常感谢。我理解前三个步骤，但在最后一步（再次转换为宽）rowid(REF) 究竟做了什么？你写它是为了编号，但如果我只执行rowid(REF) 输出是1 1 1 1?

rowid(REF) 使用 REF 作为分组列创建行号。所以每组中的第一行得到 1，第二行得到 2，依此类推……这个数字用作值列的后缀。查看?rowid() 和rowid(DT.melt$REF) 的输出了解更多信息。

也许更易读的是您将最后一行（使用 dcast）替换为以下两行：DT.melt[, number := rowid(REF)]; dcast(DT.melt, CHROM + POS + REF + RO ~ number, value.var = list("ALT", "AO", "AOF"))

【参考方案2】：

这里是dplyr 解决方案。花了我一些时间，我需要一些帮助pivot_wider dissolves arrange：

library(dplyr)
library(tidyr)

df1 %>% 
  mutate(id = row_number()) %>% 
  unite("conc1", c(ALT_1, AO_1, AOF_1), sep = "_") %>% 
  unite("conc2", c(ALT_2, AO_2, AOF_2), sep = "_") %>% 
  unite("conc3", c(ALT_3, AO_3, AOF_3), sep = "_") %>% 
  unite("conc4", c(ALT_4, AO_4, AOF_4), sep = "_") %>% 
  pivot_longer(
    starts_with("conc")
  ) %>% 
  mutate(value = ifelse(value=="NA_NA_NA", NA_character_, value)) %>% 
  group_by(id) %>% 
  mutate(value = sort(value, na.last = TRUE)) %>% 
  ungroup() %>% 
  pivot_wider(
    names_from = name,
    values_from = value,
    values_fill = "0"
  ) %>% 
  separate(conc1, c("ALT_1", "AO_1", "AOF_1"), sep = "_") %>% 
  separate(conc2, c("ALT_2", "AO_2", "AOF_2"), sep = "_") %>% 
  separate(conc3, c("ALT_3", "AO_3", "AOF_3"), sep = "_") %>% 
  separate(conc4, c("ALT_4", "AO_4", "AOF_4"), sep = "_") %>% 
  select(CHROM, POS, REF, RO, starts_with("ALT"), starts_with("AO_"), starts_with("AOF_")) %>% 
  type.convert(as.is=TRUE)

  CHROM                     POS REF      RO ALT_1 ALT_2 ALT_3 ALT_4  AO_1  AO_2  AO_3  AO_4 AOF_1 AOF_2 AOF_3 AOF_4
  <chr>                   <int> <chr> <int> <chr> <chr> <chr> <chr> <int> <int> <int> <int> <dbl> <dbl> <dbl> <dbl>
1 scaffold1000|size223437   666 A        20 AGT   CAG   G     GAT     101    12     6    13  66.4  7.89  3.95  8.55
2 scaffold1000|size223437  1332 TA       14 TGA   TGC   NA    NA        5     4    NA    NA  21.7 17.4  NA    NA   
3 scaffold1000|size223437  3445 CTTGA     9 AGC   CGC   TGA   NA       67    34    18    NA  52.3 26.6  14.1  NA   
4 scaffold1000|size223437  4336 GCTA     25 T     NA    NA    NA      120    NA    NA    NA  82.8 NA    NA    NA   

【讨论】：

非常感谢它完美运行，我理解这些步骤！