plot_PCA {proBatch} | R Documentation

## plot PCA plot

### Description

plot PCA plot

### Usage

    plot_PCA(data_matrix, sample_annotation,
      feature_id_col = "peptide_group_label", color_by = "MS_batch",
      PC_to_plot = c(1, 2), fill_the_missing = 0,
      colors_for_factor = NULL, theme = "classic", plot_title = NULL)

### Arguments

`data_matrix` | features (in rows) vs samples (in columns) matrix, with feature IDs in rownames and file/sample names as colnames. in most function, it is assumed that this is the log transformed version of the original data
`sample_annotation` | data matrix with 1) `sample_id_col` (this can be repeated as row names) 2) biological and 3) technical covariates (batches etc)
`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.
`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` | boolean value determining if missing values should be substituted with -1 (and colored with black)
`colors_for_factor` | named vector of colors for the `color_by` variable
`theme` | ggplot theme, by default `classic`. Can be easily overriden (see examples)
`plot_title` | Title of the plot (usually, processing step + representation level (fragments, transitions, proteins))

### Value

ggplot scatterplot colored by factor levels of column specified in `factor_to_color`

### See Also

`autoplot.pca_common`, `ggplot`

### Examples

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

[Package proBatch version 1.0.0 Index]