plot_corr_matrix: Visualise correlation matrix

In proBatch: Tools for Diagnostics and Corrections of Batch Effects in Proteomics

Description

recommended for heatmap-type visualisation of correlation matrix with <100 items. With >50 samples and ~10 replicate pairs distribution plots may be more informative.

Usage

plot_corr_matrix(
  corr_matrix,
  annotation = NULL,
  annotation_id_col = "FullRunName",
  factors_to_plot = NULL,
  cluster_rows = FALSE,
  cluster_cols = FALSE,
  heatmap_color = colorRampPalette(rev(brewer.pal(n = 7, name = "RdYlBu")))(100),
  color_list = NULL,
  filename = NULL,
  width = 7,
  height = 7,
  units = c("cm", "in", "mm"),
  plot_title = NULL,
  ...
)

Arguments

corr_matrix	square correlation matrix
annotation	data frame with peptide_annotation for protein correlation heatmap or sample_annotation for sample correlation heatmap
annotation_id_col	feature_id_col for protein correlation heatmap or sample_id_col for sample correlation heatmap
factors_to_plot	vector of technical and biological covariates to be plotted in this diagnostic plot (assumed to be present in sample_annotation)
cluster_rows	boolean values determining if rows should be clustered or hclust object
cluster_cols	boolean values determining if columns should be clustered or hclust object
heatmap_color	vector of colors used in heatmap.
color_list	list, as returned by sample_annotation_to_colors, where each item contains a color vector for each factor to be mapped to the color.
filename	path where the results are saved. If null the object is returned to the active window; otherwise, the object is save into the file. Currently only pdf and png format is supported
width	option determining the output image width
height	option determining the output image width
units	units: 'cm', 'in' or 'mm'
plot_title	title of the plot (e.g., processing step + representation level (fragments, transitions, proteins) + purpose (meanplot/corrplot etc))
...	parameters for the pheatmap visualisation, for details see examples and help to corresponding functions

Details

Plot correlation of selected samples or peptides

Value

pheatmap object

See Also

pheatmap, plot_sample_corr_distribution, plot_peptide_corr_distribution

Examples

peptides <- c("10231_QDVDVWLWQQEGSSK_2", "10768_RLESELDGLR_2")
data_matrix_sub = example_proteome_matrix[peptides,]
corr_matrix = cor(t(data_matrix_sub), use = 'complete.obs')
corr_matrix_plot <- plot_corr_matrix(corr_matrix)

proBatch documentation built on Nov. 8, 2020, 4:55 p.m.