tidyplate
The input xlsx or csv should be formatted in a specific way:
If the input file is an xlsx file it reads the first sheet by
default. Users can specify sheet using the sheet
argument
for an xlsx file. Users can also specify the variable name of column
where well ids will be stored (defaults to “well”). Please make sure
that well_id
argument does not match individual plate names
in the input file.
Start by loading tidyplate:
First check if the input file is valid or not:
library(tidyplate)
file <- system.file("extdata",
"example_12_well.xlsx",
package = "tidyplate")
check_plate(file) # No error for valid file
#> example_12_well.xlsx: OK; Plate type: 12-well
incorrect_file <- system.file("extdata",
"incorrect_format.csv",
package = "tidyplate")
check_plate(incorrect_file) # Error type displayed
#> Error:
#> ! Verify row and column ids in incorrect_format.csv.
#> ℹ Expected column ids: 1, 2, 3, and so on.
#> ℹ Expected row ids: A, B, C, and so on.
#> ℹ Use the `build_plate()` function to build an empty template.
As mentioned above, the formatting of the input file is very
important. A csv or excel template for each plate type can be created
using the build_plate
function:
If you want to retrieve the names of individual plates:
Read and import the file as a tibble:
data <- tidy_plate(file)
#> Plate type: 12-well
head(data)
#> # A tibble: 6 × 4
#> well drug cell_line percent_survived
#> <chr> <chr> <chr> <int>
#> 1 A01 Neomycin HEK293 60
#> 2 A02 Puromycin HEK293 NA
#> 3 A03 Neomycin Hela 52
#> 4 A04 Puromycin Hela 18
#> 5 B01 Neomycin HEK293 62
#> 6 B02 Puromycin HEK293 23
Conversely, a dataframe or tibble can be re-exported back to a plate shaped csv or xlsx file:
For more information on how to use functions on multiple files or
multi-sheet excel files read the vignette("advanced")
.