plot_sample_corr_heatmap: Sample correlation matrix (heatmap)

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

Description

Plot correlation of selected samples

Usage

plot_sample_corr_heatmap(
  data_matrix,
  samples_to_plot = NULL,
  sample_annotation = NULL,
  sample_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 = NA,
  height = NA,
  units = c("cm", "in", "mm"),
  plot_title = sprintf("Correlation matrix of%s samples",
    ifelse(is.null(samples_to_plot), "", " selected")),
  ...
)

Arguments

data_matrix	features (in rows) vs samples (in columns) matrix, with feature IDs in rownames and file/sample names as colnames. See "example_proteome_matrix" for more details (to call the description, use help("example_proteome_matrix"))
samples_to_plot	string vector of samples in data_matrix to be used in the plot
sample_annotation	data frame with: sample_id_col (this can be repeated as row names) biological covariates technical covariates (batches etc) . See help("example_sample_annotation")
sample_id_col	name of the column in sample_annotation table, where the filenames (colnames of the data_matrix are found).
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

Value

pheatmap object

See Also

pheatmap

Examples

specified_samples = example_sample_annotation$FullRunName[
which(example_sample_annotation$order %in% 110:115)] 

sample_corr_heatmap <- plot_sample_corr_heatmap(example_proteome_matrix, 
samples_to_plot = specified_samples, 
factors_to_plot = c('MS_batch','Diet', 'DateTime', 'digestion_batch'),
 cluster_rows= FALSE, cluster_cols=FALSE,
 annotation_names_col = TRUE, annotation_legend = FALSE, 
 show_colnames = FALSE)
 
 
 color_list <- sample_annotation_to_colors (example_sample_annotation, 
factor_columns = c('MS_batch','EarTag', "Strain", 
"Diet", "digestion_batch", "Sex"),
numeric_columns = c('DateTime', 'order'))
 sample_corr_heatmap_annotated <- plot_sample_corr_heatmap(log_transform_dm(example_proteome_matrix), 
 sample_annotation = example_sample_annotation,
 factors_to_plot = c('MS_batch','Diet', 'DateTime', 'digestion_batch'),
 cluster_rows= FALSE, cluster_cols=FALSE,
 annotation_names_col = TRUE, 
 show_colnames = FALSE, color_list = color_list)

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