plot_heatmap_generic: Plot the heatmap

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

Description

Plot the heatmap

Usage

plot_heatmap_generic(
  data_matrix,
  column_annotation_df = NULL,
  row_annotation_df = NULL,
  col_ann_id_col = "FullRunName",
  row_ann_id_col = "peptide_group_label",
  columns_for_cols = c("MS_batch", "Diet", "DateTime", "order"),
  columns_for_rows = c("KEGG_pathway", "WGCNA_module", "evolutionary_distance"),
  cluster_rows = FALSE,
  cluster_cols = TRUE,
  annotation_color_cols = NULL,
  annotation_color_rows = NULL,
  fill_the_missing = -1,
  color_for_missing = "black",
  heatmap_color = colorRampPalette(rev(brewer.pal(n = 7, name = "RdYlBu")))(100),
  filename = NULL,
  width = 7,
  height = 7,
  units = c("cm", "in", "mm"),
  plot_title = NULL,
  ...
)

Arguments

data_matrix	the matrix of data to be plotted
column_annotation_df	data frame annotating columns of data_matrix
row_annotation_df	data frame annotating rows of data_matrix
col_ann_id_col	column of column_annotation_df whose values are unique identifiers of columns in data_matrix
row_ann_id_col	column of row_annotation_df whose values are unique identifiers of rows in data_matrix
columns_for_cols	vector of factors (columns) of column_annotation_df that will be mapped to color annotation of heatmap columns
columns_for_rows	vector of factors (columns) of row_annotation_df that will be mapped to color annotation of heatmap rows
cluster_rows	boolean: whether the rows should be clustered
cluster_cols	boolean: whether the rows should be clustered
annotation_color_cols	list of color vectors for column annotation, for each factor to be plotted; for factor-like variables a named vector (names should correspond to the levels of factors). Advisable to supply here color list returned by sample_annotation_to_colors
annotation_color_rows	list of color vectors for row annotation, for each factor to be plotted; for factor-like variables a named vector (names should correspond to the levels of factors). Advisable to supply here color list returned by sample_annotation_to_colors
fill_the_missing	numeric value that the missing values are substituted with, or NULL if features with missing values are to be excluded.
color_for_missing	special color to make missing values. Usually black or white, depending on heatmap_color
heatmap_color	vector of colors used in heatmap (typicall a gradient)
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))
...	other parameters of link[pheatmap]{pheatmap}

Value

pheatmap-type object

Examples

p <- plot_heatmap_generic(log_transform_dm(example_proteome_matrix), 
column_annotation_df = example_sample_annotation,
columns_for_cols = c("MS_batch",  "digestion_batch", "Diet", 'DateTime'),
plot_title = 'test_heatmap',
show_rownames = FALSE, show_colnames = FALSE)

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