Mutate Sample or Variable Information — mutate

Mutate the sample or variable information tibble of an experiment().

The same syntax as dplyr::mutate() is used. For example, to add a new column to the sample information tibble, use mutate_obs(exp, new_column = value). This actually calls dplyr::mutate() on the sample information tibble with new_column = value.

If the sample column in sample_info or the variable column in var_info is to be modified, the new column must be unique, otherwise an error is thrown. The column names or row names of expr_mat will be updated accordingly.

Usage

mutate_obs(exp, ...)

mutate_var(exp, ...)

Arguments

exp: An experiment().
...: <data-masking> Name-value pairs, passed to dplyr::mutate() internally.

Value

An new experiment() object.

Examples

# Create a toy experiment for demonstration
exp <- toy_experiment()
# Add a type column to the variable information for demonstration
exp$var_info$type <- c("X", "X", "Y", "Y")

# Add a new column to sample information tibble or variable information tibble
mutate_obs(exp, new_column = c(1, 2, 3, 4, 5, 6))$sample_info
#> # A tibble: 6 × 4
#>   sample group batch new_column
#>   <chr>  <chr> <dbl>      <dbl>
#> 1 S1     A         1          1
#> 2 S2     A         2          2
#> 3 S3     A         1          3
#> 4 S4     B         2          4
#> 5 S5     B         1          5
#> 6 S6     B         2          6
mutate_var(exp, new_column = c("A", "A", "B", "B"))$var_info
#> # A tibble: 4 × 6
#>   variable protein peptide glycan_composition type  new_column
#>   <chr>    <chr>   <chr>   <chr>              <chr> <chr>     
#> 1 V1       PRO1    PEP1    H5N2               X     A         
#> 2 V2       PRO2    PEP2    H5N2               X     A         
#> 3 V3       PRO3    PEP3    N3N2               Y     B         
#> 4 V4       PRO3    PEP4    N3N2               Y     B         

# Modify existing columns
mutate_obs(exp, group = dplyr::if_else(group == "A", "good", "bad"))$sample_info
#> # A tibble: 6 × 3
#>   sample group batch
#>   <chr>  <chr> <dbl>
#> 1 S1     good      1
#> 2 S2     good      2
#> 3 S3     good      1
#> 4 S4     bad       2
#> 5 S5     bad       1
#> 6 S6     bad       2
mutate_var(exp, type = dplyr::if_else(type == "X", "good", "bad"))$var_info
#> # A tibble: 4 × 5
#>   variable protein peptide glycan_composition type 
#>   <chr>    <chr>   <chr>   <chr>              <chr>
#> 1 V1       PRO1    PEP1    H5N2               good 
#> 2 V2       PRO2    PEP2    H5N2               good 
#> 3 V3       PRO3    PEP3    N3N2               bad  
#> 4 V4       PRO3    PEP4    N3N2               bad  

# Modify the `sample` column in sample information tibble
new_exp <- mutate_obs(exp, sample = c("SI", "SII", "SIII", "SIV", "SV", "SVI"))
new_exp$sample_info
#> # A tibble: 6 × 3
#>   sample group batch
#>   <chr>  <chr> <dbl>
#> 1 SI     A         1
#> 2 SII    A         2
#> 3 SIII   A         1
#> 4 SIV    B         2
#> 5 SV     B         1
#> 6 SVI    B         2
new_exp$expr_mat
#>    SI SII SIII SIV SV SVI
#> V1  1   5    9  13 17  21
#> V2  2   6   10  14 18  22
#> V3  3   7   11  15 19  23
#> V4  4   8   12  16 20  24

# Modify the `variable` column in variable information tibble
new_exp <- mutate_var(exp, variable = c("VI", "VII", "VIII", "VIV"))
new_exp$var_info
#> # A tibble: 4 × 5
#>   variable protein peptide glycan_composition type 
#>   <chr>    <chr>   <chr>   <chr>              <chr>
#> 1 VI       PRO1    PEP1    H5N2               X    
#> 2 VII      PRO2    PEP2    H5N2               X    
#> 3 VIII     PRO3    PEP3    N3N2               Y    
#> 4 VIV      PRO3    PEP4    N3N2               Y    
new_exp$expr_mat
#>      S1 S2 S3 S4 S5 S6
#> VI    1  5  9 13 17 21
#> VII   2  6 10 14 18 22
#> VIII  3  7 11 15 19 23
#> VIV   4  8 12 16 20 24