plot_PVCA {proBatch} | R Documentation

## Plot variance distribution by variable

### Description

Plot variance distribution by variable

### Usage

    plot_PVCA(data_matrix, sample_annotation, sample_id_col = "FullRunName",
      feature_id_col = "peptide_group_label",
      technical_covariates = c("MS_batch", "instrument"),
      biological_covariates = c("cell_line", "drug_dose"),
      fill_the_missing = 0, threshold_pca = 0.6, threshold_var = 0.01,
      colors_for_bars = 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)
`sample_id_col` | name of the column in sample_annotation file, where the filenames (colnames of the data matrix are found)
`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.
`technical_covariates` | vector `sample_annotation` column names that are technical covariates
`biological_covariates` | vector `sample_annotation` column names, that are biologically meaningful covariates
`fill_the_missing` | numeric value that the missing values are substituted with
`threshold_pca` | the percentile value of the minimum amount of the variabilities that the selected principal components need to explain
`threshold_var` | the percentile value of weight each of the covariates needs to explain (the rest will be lumped together)
`colors_for_bars` | four-item color vector, specifying colors for the following categories: c('residual', 'biological', 'biol:techn', 'technical')
`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

list of two items: plot =gg, df = pvca_res

### See Also

`sample_annotation_to_colors`, `ggplot`

### Examples

    matrix <- example_proteome_matrix[1:50, ]
    pvca_plot <- plot_PVCA(matrix, example_sample_annotation,
    technical_covariates = c('MS_batch', 'digestion_batch'),
    biological_covariates = c("Diet", "Sex", "Strain"))

[Package proBatch version 1.0.0 Index]