PCA_Clus: PCA_Clus

Description Usage Arguments Value Examples

View source: R/S_PCA_Clus.R

Description

Principal Component Analysis and clustering of Maldi_Tof spectra

Usage

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PCA_Clus(
  df_m,
  varCat1,
  value,
  meth = "ward",
  dist = "euclidean",
  graph = "factorMapClus",
  pc = 3,
  ni = 1,
  nf = 10
)

Arguments

ni, nf:

first and last columns corresponding to categorical variables (default values, ni=1, nf=10)

df_m:

dataframe containing peaks and metadata

dist:

distances, "euclidean", (default value), "euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski", "pearson", "spearman" or "kendall".

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"),...

meth:

clustering method, ward(default), "average" ,"single","complete‘

graph:

visual analysis, "dendf", "dendh", (dendograms) "factorMapf", "factorMaph", "factorMapClus",(factor maps) (default value, graph="factorMapClus" )

pc:

number of principal components (pc=3, default value)

Value

figures and statistics

Examples

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 pc<-PCA_Clus(df_Peaks, varCat1="Genre", value="Lactobacillus"),
           pc<-PCA_Clus(df_Peaks, varCat1="Genre", value="Lactobacillus", graph="dendh")
           pc<-PCA_Clus(df_Peaks, varCat1="Genre", value="Lactobacillus", graph="dendf"),
           pc<-PCA_Clus(df_Peaks, varCat1="Genre", value="Lactobacillus", graph="factorMapf")
    source: https://www.rdocumentation.org/packages/FactoMineR/versions/2.2/topics/PCA
           https://www.rdocumentation.org/packages/FactoMineR/versions/2.2/topics/HCPC
           http://www.sthda.com/english/articles/31-principal-component-methods-in-r-practical-guide/117-hcpc-hierarchical-clustering-on-principal-components-essentials/
           https://rpkgs.datanovia.com/factoextra/
           http://factominer.free.fr/factomethods/hierarchical-clustering-on-principal-components.html

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