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

Description Usage Arguments Value See Also Examples

View source: R/proteome_wide_diagnostics.R

plot PCA plot

plot_PCA(
  data_matrix,
  sample_annotation,
  feature_id_col = "peptide_group_label",
  sample_id_col = "FullRunName",
  color_by = "MS_batch",
  PC_to_plot = c(1, 2),
  fill_the_missing = -1,
  color_scheme = "brewer",
  filename = NULL,
  width = NA,
  height = NA,
  units = c("cm", "in", "mm"),
  plot_title = NULL,
  theme = "classic"
)

`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")`)
`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")`
`feature_id_col`	name of the column with feature/gene/peptide/protein ID used in the long format representation `df_long`. In the wide formatted representation `data_matrix` this corresponds to the row names.
`sample_id_col`	name of the column in `sample_annotation` table, where the filenames (colnames of the `data_matrix` are found).
`color_by`	column name (as in `sample_annotation`) to color by
`PC_to_plot`	principal component numbers for x and y axis
`fill_the_missing`	numeric value determining how missing values should be substituted. If `NULL`, features with missing values are excluded. If `NULL`, features with missing values are excluded.
`color_scheme`	a named vector of colors to map to `batch_col`, names corresponding to the levels of the factor. For continuous variables, vector doesn't need to be named.
`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))
`theme`	ggplot theme, by default `classic`. Can be easily overriden

ggplot scatterplot colored by factor levels of column specified in factor_to_color

autoplot.pca_common, ggplot

pca_plot <- plot_PCA(example_proteome_matrix, example_sample_annotation, 
color_by = 'MS_batch', plot_title = "PCA colored by MS batch")
pca_plot <- plot_PCA(example_proteome_matrix, example_sample_annotation, 
color_by = 'DateTime', plot_title = "PCA colored by DateTime")

color_list <- sample_annotation_to_colors (example_sample_annotation, 
factor_columns = c('MS_batch', 'digestion_batch'),
numeric_columns = c('DateTime','order'))
pca_plot <- plot_PCA(example_proteome_matrix, example_sample_annotation, 
color_by = 'DateTime', color_scheme = color_list[['DateTime']])

## Not run: 
pca_plot <- plot_PCA(example_proteome_matrix, example_sample_annotation, 
color_by = 'DateTime', plot_title = "PCA colored by DateTime",
filename = 'test_PCA.png', width = 14, height = 9, units = 'cm')

## End(Not run)