See vignettes for further examples
label_plate_rowcol(plate, rowkey = NULL, colkey = NULL, coercefactors = TRUE)| plate | tibble (data frame) with variables well_row, well_col, well. This would usually be produced by create_blank_plate(). It is possible to include other information in additional variables. |
|---|---|
| rowkey | tibble (data frame) describing plate rows, with variables well_row and others. |
| colkey | tibble (data frame) describing plate columns, with variables well_col and others. |
| coercefactors | if TRUE, coerce well_row in rowkey and well_col in colkey to factors |
tibble (data frame) with variables well_row, well_col, well, and others.
This tibble contains all combinations of well_row and well_col found in the input plate, and all information supplied in rowkey and colkey distributed across every well of the plate. Return plate is ordered by row well_row then column well_col.
Note this ordering may cause a problem if well_col is supplied as a character (1,10,11,...), instead of a factor or integer (1,2,3,...). For this reason, the function by default converts well_row in `rowkey`, and well_col in `colkey`, to factors, taking factor levels from `plate`, and warns the user.
Other tidyqpcr functions require plate plans to contain variables sample_id, target_id, and prep_type, so `label_plate_rowcol` will warn if any of these are missing. This is a warning, not an error, because these variables can be added by users later.
Other plate creation functions:
create_blank_plate(),
create_colkey_4diln_2ctrl_in_24(),
create_colkey_6_in_24(),
create_colkey_6diln_2ctrl_in_24(),
create_rowkey_4_in_16(),
create_rowkey_8_in_16_plain(),
display_plate()
label_plate_rowcol(plate = create_blank_plate()) # returns blank plate
#> Warning: plate does not contain variable sample_id
#> Warning: plate does not have variable target_id
#> Warning: plate does not have variable prep_type
#> # A tibble: 384 x 3
#> well well_row well_col
#> <chr> <fct> <fct>
#> 1 A1 A 1
#> 2 A2 A 2
#> 3 A3 A 3
#> 4 A4 A 4
#> 5 A5 A 5
#> 6 A6 A 6
#> 7 A7 A 7
#> 8 A8 A 8
#> 9 A9 A 9
#> 10 A10 A 10
#> # … with 374 more rows