PointClusterVal: PointClusterVal

In Sautie/MALDITOFSpectraPA: Processing and analysis of MALDI_TOF spectra

Description

wrapper of functions for clustering tendency and validation statistics

Usage

PointClusterVal(
  df_m,
  meth = "hclust",
  dist = "euclidean",
  meth2 = "ward.D2",
  varCat1,
  value,
  varCat2
)

Arguments

df_m:	dataframe containing peaks and metadata
meth:	clustering algorithms ("hclust", default value), other values: "kmeans", "pam", "clara", "fanny", "hclust","agnes", "diana"
dist:	distances ("euclidean", default value), "maximum", "manhattan", "canberra", "binary" "minkowski"
meth2:	hc methods ("ward.D2", default value), average", "ward.D", "single", "complete", "mcquitty", "median" or "centroid"
varCat1:	categorical variable for choosing isolates, examples: "Taxonomie","Genre","Date.d.analyse","Origine","Ruche", "Nutrition", "Date.de.récolte", "Lieu.de.la.ruche"
value:	level of catVar1, examples: "Lactobacillus" ("Genre"), Taxonomie("Pediococcus pentosaceus"), "Erica cinerea" ("Nutrition"),...
varCat2:	categorical variable for partitioning the set of isolates chosen by using varCat1

Value

figures and statistics

Examples

   ff<-PointClusterVal(df_Peaks, varCat1="Genre", value="Lactobacillus", varCat2="Nutrition")
       source:https://www.rdocumentation.org/packages/fpc/versions/2.2-8/topics/cluster.stats
              https://www.datanovia.com/en/lessons/cluster-validation-statistics-must-know-methods/

Sautie/MALDITOFSpectraPA documentation built on Dec. 31, 2020, 4:28 p.m.