head(data) #> # A tibble: 6 x 6 #> Plate Wells Drug Concentration Bacteria Killing #> #> 1 Experiment 1 A01 A 100 E. # same file as above file1 tibble (S3: tbl_df/tbl/ame) #> $ Plate : chr "Experiment 1" "Experiment 1" "Experiment 1" "Experiment 1".
coliĪdd_plate then makes it easy to store data in a mix of formats, in some cases tidy and in some cases plate-shaped, which is the reality of many experiments.
head(data2) #> # A tibble: 6 x 5 #> Wells Killing Drug Concentration Bacteria #> #> 1 A01 98 A 100 E. Now, each well is represented by a single row, with the values indicated in the file for each column.įile2A 'ame': 96 obs.
It additionally creates a column named “Wells” with the well identifiers for each well. So you have four columns: Drug, Concentration, Bacteria, and Killing. So what happened? read_plate() read in the plater format file you created and turned each layout into a column, using the name of the layout specified in the file. head(data) #> Wells Drug Concentration Bacteria Killing #> 1 A01 A 100.000 E. File_path Classes 'tbl_df', 'tbl' and 'ame': 96 obs.
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