For more help, examples and explanations, see the plate setup vignette:
vignette("platesetup_vignette", package = "tidyqpcr")
Arguments
- 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
Value
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 messages the user.
If `plate$well_col` or `plate$well_row` are not factors and coercefactors = TRUE label_plate_rowcol will automatically convert them to factors, but will output a warning telling users this may lead to unexpected behaviour.
Other tidyqpcr functions require plate plans to contain variables sample_id, target_id, and prep_type, so `label_plate_rowcol` will message if any of these are missing. This is a message, not an error, because these variables can be added by users later.
Details
For worked examples of tidyqpcr analysis with 384-well plates, see:
vignette("calibration_vignette", package = "tidyqpcr")
See also
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_qpcr(),
display_plate_value(),
display_plate(),
make_row_names_echo1536(),
make_row_names_lc1536()
Examples
label_plate_rowcol(plate = create_blank_plate()) # returns blank plate
#> plate does not contain variable sample_id
#> plate does not have variable target_id
#> plate does not have variable prep_type
#> # A tibble: 384 × 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
#> # ℹ 374 more rows
# label blank 96-well plate with empty edge wells
label_plate_rowcol(plate = create_blank_plate(well_row = LETTERS[2:7],
well_col = 2:11))
#> plate does not contain variable sample_id
#> plate does not have variable target_id
#> plate does not have variable prep_type
#> # A tibble: 60 × 3
#> well well_row well_col
#> <chr> <fct> <fct>
#> 1 B2 B 2
#> 2 B3 B 3
#> 3 B4 B 4
#> 4 B5 B 5
#> 5 B6 B 6
#> 6 B7 B 7
#> 7 B8 B 8
#> 8 B9 B 9
#> 9 B10 B 10
#> 10 B11 B 11
#> # ℹ 50 more rows
# label 96-well plate with sample id in rows
label_plate_rowcol(plate = create_blank_plate(well_row = LETTERS[1:8],
well_col = 1:12),
rowkey = tibble(well_row = LETTERS[1:8],
sample_id = paste0("S_",1:8)))
#> coercing well_row to a factor with levels from plate$well_row
#> plate does not have variable target_id
#> plate does not have variable prep_type
#> # A tibble: 96 × 4
#> well well_row well_col sample_id
#> <chr> <fct> <fct> <chr>
#> 1 A1 A 1 S_1
#> 2 A2 A 2 S_1
#> 3 A3 A 3 S_1
#> 4 A4 A 4 S_1
#> 5 A5 A 5 S_1
#> 6 A6 A 6 S_1
#> 7 A7 A 7 S_1
#> 8 A8 A 8 S_1
#> 9 A9 A 9 S_1
#> 10 A10 A 10 S_1
#> # ℹ 86 more rows
# label fraction of 96-well plate with target id in columns
label_plate_rowcol(plate = create_blank_plate(well_row = LETTERS[1:8],
well_col = 1:4),
colkey = tibble(well_col = 1:4,
target_id = paste0("T_",1:4)))
#> coercing well_col to a factor with levels from plate$well_col
#> plate does not contain variable sample_id
#> plate does not have variable prep_type
#> # A tibble: 32 × 4
#> well well_row well_col target_id
#> <chr> <fct> <fct> <chr>
#> 1 A1 A 1 T_1
#> 2 A2 A 2 T_2
#> 3 A3 A 3 T_3
#> 4 A4 A 4 T_4
#> 5 B1 B 1 T_1
#> 6 B2 B 2 T_2
#> 7 B3 B 3 T_3
#> 8 B4 B 4 T_4
#> 9 C1 C 1 T_1
#> 10 C2 C 2 T_2
#> # ℹ 22 more rows