This vignette shows how to generate a row-column Design using both the FielDHub Shiny App and the scripting function
row_column() from the
To generate a Row-Column Design using the FielDHub app:
First, go to Lattice Designs > Resolvable Row-Column Design (RCD)
Then, follow the following steps where we will show how to generate a Row-Column Design with 45 treatments, 5 rows and 3 reps.
Import entries’ list? Choose whether to import a list with entry numbers and names for genotypes or treatments.
If the selection is
No, that means the app is going to generate synthetic data for entries and names of the treatment based on the user inputs.
If the selection is
Yes, the entries list must fulfill a specific format and must be a
.csvfile. The file must have the columns
ENTRYcolumn must have a unique entry integer number for each treatment. The column
NAMEmust have a unique name that identifies each treatment. Both
NAMEmust be unique, duplicates are not allowed. In the following table, we show an example of the entries list format. This example has an entry list with 12 treatments.
Input the number of treatments in the Input # of Treatments box. We will enter
45for our sample experiment.
Set the number of plots in each incomplete block with the Input # of Plots per IBlock box. In this examples, set it to
Select the number of replications of these treatments with the Input # of Full Reps box. In this examples, set it to
Enter the number of locations in Input # of Locations. We will run this experiment over a single location, so set it to
cartesianin the Plot Order Layout. For this example we will use the default
Enter the starting plot number in the Starting Plot Number box. If the experiment has multiple locations, you must enter a comma separated list of numbers the length of the number of locations for the input to be valid. Set it to
Enter a name for the location of the experiment in the Input Location box. If there are multiple locations, each name must be in a comma separated list. For this example, set it to
To ensure that randomizations are consistent across sessions, we can set a seed number in the box labeled Seed Number. In this example, we will set it to
Once we have entered the information for our experiment on the left side panel, click the Run! button to run the design.
After you run a row-column design in FielDHub, there are several ways to display the information contained in the field book.
When you first click the run button on a row-column design, FielDHub displays the Field Layout tab, which shows the entries and their arrangement in the field. In the box below the display, you can change the layout of the field. You can also display a heatmap over the field by changing Type of Plot to
Heatmap. To view a heatmap, you must first simulate an experiment over the described field with the Simulate! button. A pop-up window will appear where you can enter what variable you want to simulate along with minimum and maximum values.
The Field Book displays all the information on the experimental design in a table format. It contains the specific plot number and the row and column address of each entry, as well as the corresponding treatment on that plot. This table is searchable, and we can filter the data in relevant columns. If we have simulated data for a heatmap, an additional column for that variable appears in the field book.
You can run the same design with a function in the FielDHub package,
First, you need to load the
FielDHub package by typing
Then, you can enter the information describing the above design like this:
rcd <- row_column( t = 45, nrows = 5, r = 3, l = 1, plotNumber = 101, locationNames = "FARGO", seed = 1244 )
The description for the inputs that we used to generate the design,
t = 45is the number of treatments.
nrows = 5is the number of rows.
r=3is the number of reps
l = 1is the number of locations.
plotNumber = 101is the starting plot number.
locationNames = "FARGO"is an optional name for each location.
seed = 1244is the seed number to replicate identical randomizations.
To print a summary of the information that is in the object
rcd, we can use the generic function
Row Column Design Information on the design parameters: List of 7 $ rows : num 5 $ columns : num 9 $ reps : num 3 $ treatments : num 45 $ locations : num 1 $ location_names: chr "FARGO" $ seed : num 1244 10 First observations of the data frame with the row_column field book: ID LOCATION PLOT REP ROW COLUMN ENTRY TREATMENT 1 1 FARGO 101 1 1 1 39 G-39 2 2 FARGO 102 1 1 2 5 G-5 3 3 FARGO 103 1 1 3 19 G-19 4 4 FARGO 104 1 1 4 12 G-12 5 5 FARGO 105 1 1 5 33 G-33 6 6 FARGO 106 1 1 6 45 G-45 7 7 FARGO 107 1 1 7 41 G-41 8 8 FARGO 108 1 1 8 25 G-25 9 9 FARGO 109 1 1 9 23 G-23 10 10 FARGO 110 1 2 1 43 G-43
row_column() function returns a list consisting of all the information displayed in the output tabs in the FielDHub app: design information, plot layout, plot numbering, entries list, and field book. These are accessible by the
$ operator, i.e.
rcd$fieldBook is a list containing information about every plot in the field, with information about the location of the plot and the treatment in each plot. As seen in the output below, the field book has columns for
field_book <- rcd$fieldBook head(rcd$fieldBook, 10)
ID LOCATION PLOT REP ROW COLUMN ENTRY TREATMENT 1 1 FARGO 101 1 1 1 39 G-39 2 2 FARGO 102 1 1 2 5 G-5 3 3 FARGO 103 1 1 3 19 G-19 4 4 FARGO 104 1 1 4 12 G-12 5 5 FARGO 105 1 1 5 33 G-33 6 6 FARGO 106 1 1 6 45 G-45 7 7 FARGO 107 1 1 7 41 G-41 8 8 FARGO 108 1 1 8 25 G-25 9 9 FARGO 109 1 1 9 23 G-23 10 10 FARGO 110 1 2 1 43 G-43