在一列中基于相似值重新构造data.frame

Question

我有一个带有2列的data.frame，其中第二列中的值是重复的。例如：

     HUGO                     Cell
1    CD28                 T cells
2    CD3D                 T cells
3    CD3G                 T cells
4    CD8A                lymphocytes
5    EOMES               lymphocytes
6    FGFBP2              lymphocytes
7    GNLY                lymphocytes
8    NCR1                 NK cells
9    PTGDR                NK cells
10   SH2D1B               NK cells

我希望与列单元格中唯一名称对应的列HUGO中的所有值在每个唯一名称之后进入名称列表。

例如

T cells: CD28     CC3D     C34
lymphocytes: CD8A    EOMES    FGFBP2  FGFBP2    GNLY 
... 

我试过了

reshape(data.frame, timevar = "HUGO",idvar = "Cell",direction = "wide")，但它只返回单元格列中每个名称的值数。

Answer 1

这里有一些可能性取决于你想要的是什么。前5不使用包。

1)聚合/c--这给出了一个数据框架，其第二列是HUGO的字符向量。

aggregate(HUGO ~ Cell, DF, c)

给予：

         Cell                      HUGO
1 lymphocytes CD8A, EOMES, FGFBP2, GNLY
2    NK cells       NCR1, PTGDR, SH2D1B
3     T cells          CD28, CD3D, CD3G

2)聚合/toString--这给出了一个数据框架，它的第二列包含用逗号分隔HUGO的字符串。

aggregate(HUGO ~ Cell, DF, toString)

给予：

         Cell                      HUGO
1 lymphocytes CD8A, EOMES, FGFBP2, GNLY
2    NK cells       NCR1, PTGDR, SH2D1B
3     T cells          CD28, CD3D, CD3G

3)这给出了一个列表，每个单元格都有一个组件，每个组件都是该单元格的HUGO名称。

unstack(DF)

给予：

$lymphocytes
[1] "CD8A"   "EOMES"  "FGFBP2" "GNLY"  

$`NK cells`
[1] "NCR1"   "PTGDR"  "SH2D1B"

$`T cells`
[1] "CD28" "CD3D" "CD3G"

4)这给出了一个矩阵，它的行是单元格，其列是HUGO名称的序号。

DF2 <- transform(DF, seq = ave(seq_along(HUGO), Cell, FUN t= seq_along))
tapply(DF2$HUGO, DF2[-1], c)

给予：

             seq
Cell          1      2       3        4     
  lymphocytes "CD8A" "EOMES" "FGFBP2" "GNLY"
  NK cells    "NCR1" "PTGDR" "SH2D1B" NA    
  T cells     "CD28" "CD3D"  "CD3G"   NA   

5)重塑--使用最后一个选项的DF2与reshape一起给出一个数据框架：

reshape(DF2, timevar = "seq", idvar = "Cell", dir = "wide")

给予：

         Cell HUGO.1 HUGO.2 HUGO.3 HUGO.4
1     T cells   CD28   CD3D   CD3G   <NA>
4 lymphocytes   CD8A  EOMES FGFBP2   GNLY
8    NK cells   NCR1  PTGDR SH2D1B   <NA>

6)扩展--这给出了一个"tbl_df"类对象作为输出(它是"data.frame"的子类)

library(dplyr)
library(tidyr)

DF %>% 
   group_by(Cell) %>%
   mutate(seq = 1:n()) %>%
   ungroup() %>%
   spread(seq, HUGO)

给予：

         Cell    1     2      3    4
1 lymphocytes CD8A EOMES FGFBP2 GNLY
2    NK cells NCR1 PTGDR SH2D1B <NA>
3     T cells CD28  CD3D   CD3G <NA>

7) read.zoo read.zoo给出了一个以细胞为时间的动物园物体。

由于时间实际上是字符串，所以我们使用FUN=identity来避免解释。fortify.zoo将其转换为数据帧。DF2来自上面。

library(zoo)

fortify.zoo(read.zoo(DF2, split = "seq", index = "Cell", FUN = identity))

给予：

       Index    1     2      3    4
1 lymphocytes CD8A EOMES FGFBP2 GNLY
2    NK cells NCR1 PTGDR SH2D1B <NA>
3     T cells CD28  CD3D   CD3G <NA>

8) dcast --这给出了一个data.table作为输出。

library(data.table)

DT <- data.table(DF)
DT[, seq:=1:.N, by = Cell]
dcast(DT, Cell ~ seq, value.var = "HUGO")

给予：

          Cell    1     2      3    4
1:    NK cells NCR1 PTGDR SH2D1B   NA
2:     T cells CD28  CD3D   CD3G   NA
3: lymphocytes CD8A EOMES FGFBP2 GNLY

注：

DF <- structure(list(HUGO = c("CD28", "CD3D", "CD3G", "CD8A", "EOMES", 
"FGFBP2", "GNLY", "NCR1", "PTGDR", "SH2D1B"), Cell = c("T cells", 
"T cells", "T cells", "lymphocytes", "lymphocytes", "lymphocytes", 
"lymphocytes", "NK cells", "NK cells", "NK cells")), .Names = c("HUGO", 
"Cell"), class = "data.frame", row.names = c(NA, -10L))