Shiny app for exploring clustering solutions — pandemonium • pandemonium

Opening the GUI to cluster the data points based on the predictions. Coordinates and distances are computed on the fly, or can be entered in the function call.(modified)

Usage

pandemonium(
  df,
  cov = NULL,
  is.inv = FALSE,
  exp = NULL,
  space2 = NULL,
  space2.cov = NULL,
  space2.exp = NULL,
  group = NULL,
  label = NULL,
  user_dist = NULL,
  dimReduction = list(tSNE = tSNE, umap = umap),
  getCoords = list(normal = normCoords),
  getScore = NULL
)

Arguments

df: data frame of data assumes space 1 but variables can be changed once loaded
cov: covariance matrix (optional)
is.inv: is the covariance matrix an inverse default FALSE
exp: observable reference value (e.g. experimental measurement)
space2: dataframe assumed to be in space 2 but can be changed when loaded
space2.cov: covariance matrix (optional)
space2.exp: observable reference value (e.g. experimental measurement)
group: grouping assignments
label: point labels
user_dist: input distance matrix (optional)
dimReduction: named list functions used for dimension reduction.
getCoords: named list containing functions to calculate coordinates
getScore: named list contaiining functions to calculate scores to be plotted as bins and continuous value.