wrapperWPM {wpm} | R Documentation |
Wrapper function that generates plate plans like the wpm shiny application. This feature allows the user to use the wpm package from the command line rather than going through a web application.
wrapperWPM( user_df, plate_dims, nb_plates, forbidden_wells = NULL, buffer_wells = NULL, fixed_wells = NULL, spatial_constraint = "none", max_iteration = 20 )
user_df |
dataframe containing user data obtained with the 'convertCSV()' or 'convertESet()' functions. |
plate_dims |
list, containing 2 values: the first is the number of plate's lines and second is the number of plate's columns. |
nb_plates |
numeric, corresponds to the number of plates to fill |
forbidden_wells |
character, the wells that will not be used at all for the experiment. This argument needs to be a character string giving the wells coordinates of the form "LetterNumber" (eg. "A1" for the well positionned in the first row/ first column of the plate). |
buffer_wells |
character, the wells that will be used during experiment but without biological sample in it. Same input structure as for forbidden_wells parameter. |
fixed_wells |
character, the wells that will be used for Quality Control samples or standards during the Experiment. Same input structure as for forbidden_wells parameter. |
spatial_constraint |
character, is the spatial constraint used to place the samples on the plate. It can also be called neighborhood constraint. Currently, the possible values are "none", "NS" (for North-South), "WE" (for West-East) and "NEWS" (North-South-East-West). |
max_iteration |
numeric, maximal number of attemps for wpm to find a valid solution. |
a dataframe if wpm finds a solution.
# create a MSnSet toy example sample_names <- c("s1","s2","s3","s4", "s5") M <- matrix(NA, nrow = 4, ncol = 5) colnames(M) <- sample_names rownames(M) <- paste0("id", LETTERS[1:4]) pd <- data.frame(Environment = rep_len(LETTERS[1:3], 5), Category = rep_len(1:2, 5), row.names = sample_names) rownames(pd) <- colnames(M) x <- MSnbase::MSnSet(exprs = M,pData = pd) # convert it to a valid dataframe for wpm df <- convertESet(x, "Environment") # run wpm on the toy example wrapperWPM(user_df = df, plate_dims = list(8,12), nb_plates = 1, forbidden_wells = "A1,A2,A3", fixed_wells = "B1,B2", spatial_constraint = "NS")