The relsa_wrapper analyses the data set and calculates various RELSA objects for later analysis.
Please note that the data must be in the RELSA format.
relsa_wrapper( querydata, baseline = NULL, treatment = NULL, condition = NULL, normthese = NULL, turnsQuery = NULL, dropsQuery = NULL, animalnr = 1, ymax = 1.2, ymin = 0, pcadims = 2, studylabel = NULL, severity = NULL, colorlabel = NULL, doPCA = TRUE, showScree = "yes", showPlot = "no", k = 6 )
| querydata | dataset sample data frame |
|---|---|
| baseline | cluster baselines from |
| treatment | treatment column, potential data filter for subsampling (use column name as character, e.g. "transmitter") |
| condition | condition column, potential data filter for subsampling (use column name as character, e.g. "Carprofen") |
| normthese | variable vector (colum names as character, e.g. c("hr","temp")) with the names of the variables that need "normalization" |
| turnsQuery | variable vector (colum names as character, e.g. c("hr","temp")) with the names of the variables that need "turning" |
| dropsQuery | variables to drop |
| animalnr | animal number (not id) in the data set for which an example RELSA flow is generated (defaults to 1) |
| ymax | y-max of the y axis (defaults to 1.2) |
| ymin | y-min of the y axis (defaults to 0) |
| pcadims | for how many principal components shall the dimensional contributions be calculated (note: only 2 can be plotted, defaults to 2) |
| studylabel | you can assign an individual study name to label some of the tables in the relsa object |
| severity | you can assign a prospective severity for your experiment (has no effect on model calculations, just information) |
| colorlabel | you can assign a color label to some tables of the relsa object |
| doPCA | calculate the PCA or skip |
| showScree | shows the scree plot (gets overwritten by showPlot) |
| showPlot | shows the k-means plot (ordered) |
| k | the number of k-clusters in the k-means analysis |
robj RELSA object - a list with RELSA calculation outputs.