PomaMultivariate {POMA} | R Documentation

## Multivariate Statistical Methods for Mass Spectrometry Data

### Description

PomaMultivariate() allows users to perform different multivariate statistical analysis on MS data.

### Usage

    PomaMultivariate(
      data,
      method = "pca",
      components = 5,
      center = FALSE,
      scale = FALSE,
      labels = FALSE,
      load_length = 1,
      ellipse = TRUE,
      validation = "Mfold",
      folds = 5,
      nrepeat = 10,
      vip = 1.5,
      num_features = 10
    )

### Arguments

`data` | A MSnSet object. First `pData` column must be the subject group/type.
`method` | A multivariate method. Options are: "pca", "plsda" and "splsda".
`components` | Numeric. Number of components to include in the model. Default is 5.
`center` | Logical that indicates whether the variables should be shifted to be zero centered. Default is FALSE.
`scale` | Logical that indicates whether the variables should be scaled to have unit variance before the analysis takes place. Default is FALSE.
`labels` | Logical indicating if sample names should be plotted or not.
`load_length` | Numeric between 1 and 2. Define the length of biplot loadings. Default is 1.
`ellipse` | Logical that indicates whether a 95%CI ellipse should be plotted in scores plot. Default is TRUE.
`validation` | (Only for "plsda" and "splsda" methods) Validation method. Options are "Mfold" and "loo".
`folds` | (Only for "plsda" and "splsda" methods) Numeric. Number of folds for Mfold validation method (default is 5). If the validation method is loo, this value will become to 1.
`nrepeat` | (Only for "plsda" and "splsda" methods) Numeric. Number of iterations for the validation method selected.
`vip` | (Only for "plsda" method) Numeric indicating VIP cutoff to select features that will be displayed in vip plot.
`num_features` | (Only for "splsda" method) Numeric. Number of variables selected to discriminate groups.

### Value

A list with all results for multivariate statistical analysis including plots and data frames.

### Author(s)

Pol Castellano-Escuder

### Examples

    data("st000336")

    # PCA
    st000336 %>%
      PomaImpute() %>%
      PomaNorm() %>%
      PomaOutliers() %>%
      PomaMultivariate(method = "pca")

    # PLSDA
    st000336 %>%
      PomaImpute() %>%
      PomaNorm() %>%
      PomaOutliers() %>%
      PomaMultivariate(method = "plsda", vip = 1)

    # sPLSDA
    st000336 %>%
      PomaImpute() %>%
      PomaNorm() %>%
      PomaOutliers() %>%
      PomaMultivariate(method = "splsda")

[Package POMA version 1.0.0 Index]