Changing the name of elements in a column

Question

I have a very big matrix like

> head(mat[1:4,1:4])
                     Tumor_Sample_Barcode Chromosome Start_Position End_Position
1: LP6005334-DNA_H01_vs_LP6005333-DNA_H01       chr1        1026918      1026918
2: LP6005334-DNA_H01_vs_LP6005333-DNA_H01       chr1       15772155     15772155
3: LP6005334-DNA_H01_vs_LP6005333-DNA_H01       chr1       16054813     16054813
4: LP6005334-DNA_H01_vs_LP6005333-DNA_H01       chr1       24120222     24120222

> dim(mat)
[1] 450754     53
>

In Tumor_Sample_Barcode column I have the name of samples so that

> unique(mat$Tumor_Sample_Barcode)
 [1] "LP6005334-DNA_H01_vs_LP6005333-DNA_H01"     "LP6005500-DNA_D03_vs_LP6005499-DNA_D03"    
 [3] "LP6005935-DNA_G02_vs_LP6005979-DNA_C01"     "LP6007600_vs_LP6007599"                    
 [5] "LP6008202-DNA_B03_vs_LP6008201-DNA_B03"     "LP6008269-DNA_F06_vs_LP6008268-DNA_G06"    
 [7] "LP6008334-DNA_A03_vs_LP6008335-DNA_E02"     "LP6008334-DNA_A04_vs_LP6008335-DNA_E03"    
 [9] "LP6008334-DNA_B02_vs_LP6008335-DNA_F01"     "LP6008334-DNA_C02_vs_LP6008335-DNA_G01"    
[11] "LP6008334-DNA_D02_vs_LP6008335-DNA_H01"     "LP6008336-DNA_F02_vs_LP6008333-DNA_F02"    
[13] "LP6008336-DNA_G01_vs_LP6008333-DNA_G01"     "LP6008336-DNA_H01_vs_LP6008333-DNA_H01"    
[15] "LP6008336-DNA_H02_vs_LP6008333-DNA_H02"     "LP6008337-DNA_A07_vs_LP6008338-DNA_E06"    
[17] "LP6008337-DNA_H06_vs_LP6008338-DNA_D06"     "LP6008460-DNA_A04_vs_LP6008340-DNA_D05__pv"
[19] "LP6008460-DNA_D01_vs_LP6008340-DNA_E02__pv" "LP6008460-DNA_F02_vs_LP6008340-DNA_E05"    
[21] "LP6008460-DNA_G03_vs_LP6008340-DNA_C05__pv"
>

I want to change the name of these samples to A1... A21 but I don't know how

Can you help?

Thank you

Answer 1

If your data is in a dataframe you can make use of plyr. Using mapvalues() from this library, you can rename provide a list of keys and a list of values. Instead of explicitly listing the keys, we can just use unique(mat$Tumor_Sample_Barcode) [credit to @dc37]. I use the paste0 function here and the colon operator to generate the vector of A1,A2,...,A21.

Assign the vector produced by mapvalues() to the column and you're off!

install.packages("plyr")
mat$Tumor_Sample_Barcode <-
plyr::mapvalues(x=mat$Tumor_Sample_Barcode,
                from=unique(mat$Tumor_Sample_Barcode),
                to=paste0("A", 1:21))

I'd recommend keeping this column and adding a new column with your simplified sample names, but this is not what you requested.

Answer 2

Change to factor then to numeric:

mat$Tumor_Sample_Barcode <- as.numeric(as.factor(mat$Tumor_Sample_Barcode))

Using @dc37 example data:

as.numeric(as.factor(df$vect))
# [1] 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

If we need to prefix with "A"

paste0("A", as.numeric(as.factor(df$vect)))
# [1] "A1" "A2" "A3" "A4" "A1" "A2" "A3" "A4" "A1" "A2" "A3" "A4" "A1" "A2" "A3" "A4" "A1" "A2" "A3" "A4"

Or we can keep them as factors:

x <- sort(unique(df$vect))
factor(df$vect, levels = x, labels = paste0("A", seq_along(x)))
# [1] A1 A2 A3 A4 A1 A2 A3 A4 A1 A2 A3 A4 A1 A2 A3 A4 A1 A2 A3 A4
# Levels: A1 A2 A3 A4

Answer 3

Using sub in base R, you can:

1) define the replacement vector:

vector = paste0("A",seq(1:21))

2) and loop over each levels of your first columns to replace them individually:

for(i in 1:length(levels(mat$Tumor_Sample_Barcode)))
{
  levels(mat$Tumor_Sample_Barcode)[i] = sub(levels(mat$Tumor_Sample_Barcode)[i],vector[i], levels(mat$Tumor_Sample_Barcode)[i])
}

Example:

Here, a small example to show you:

df = data.frame(vect = factor(rep(c("a","b","c","d"),5)),
                       value = rnorm(20))

> head(df)       
  vect        value
1    a  0.418186287
2    b -0.232936122
3    c  1.563349091
4    d -0.001453912
5    a -0.453995163
6    b -0.481360070

vector = paste0("A",seq(1,4))
for(i in 1:length(levels(df$vect)))
{
  levels(df$vect)[i] = sub(levels(df$vect)[i],vector[i], levels(df$vect)[i]) 
}

And you get:

> head(df)
  vect        value
1   A1  0.418186287
2   A2 -0.232936122
3   A3  1.563349091
4   A4 -0.001453912
5   A1 -0.453995163
6   A2 -0.481360070

Does it answer your question ?