View source: R/relsa_wrapper.R
relsa_wrapper | R Documentation |
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.
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