PomaCorr: Correlation Analysis

In POMA: User-friendly Workflow for Pre-processing and Statistical Analysis of Mass Spectrometry Data

Description

This function returns different correlation plots (correlogram and network plots) and a table with all pairwise correlations in the data.

Usage

PomaCorr(
  data,
  method = "pearson",
  shape = "square",
  type = "full",
  show_corr = FALSE,
  low = "#336B87",
  outline = "white",
  high = "#EA8620",
  label_size = 12,
  corr_type = "cor",
  coeff = 0.7
)

Arguments

data	A MSnSet object. First pData column must be the subject group/type.
method	Character indicating which correlation coefficient has to be computed. Options are "pearson" (default), "kendall" and "spearman".
shape	Character ingicating shape of correlogram. Options are "square" (default) and "circle".
type	Character indicating type of correlogram. Options are "full" (default), "lower" or "upper".
show_corr	Logical indicating if correlation coefficient for each pair of features should be plotted in correlogram or not (default = FALSE). Only recomended for a low number of features.
low	Colour for low end of the gradient in correlogram.
outline	Colour for the outline of the gradient in correlogram.
high	Colour for high end of the gradient in correlogram.
label_size	Numeric indicating label size in correlogram.
corr_type	Type of network to be made with correlation matrix. Options are "cor" (for global correlations) and "glasso" (for gaussian graphical model). Default is "cor". See glasso R package for the second option.
coeff	Numeric indicatin correlation coefficient. Edges with absolute weight below this value will be removed from the network. If "corr_type" is set to "glasso", this parameter indicates the regularization parameter for lasso (rho = 0 means no regularization). See glasso::glasso().

Value

A list with the results.

Author(s)

Pol Castellano-Escuder

References

Jerome Friedman, Trevor Hastie and Rob Tibshirani (2019). glasso: Graphical Lasso: Estimation of Gaussian Graphical Models. R package version 1.11. https://CRAN.R-project.org/package=glasso

Examples

data("st000284")

# pearson correlation
PomaCorr(st000284)$correlations
PomaCorr(st000284)$corrplot

# gaussian graphical model
# library(ggraph)
# PomaCorr(st000284, corr_type = "glasso")

POMA documentation built on Nov. 8, 2020, 6:26 p.m.