calculate_peptide_corr_distr {proBatch} | R Documentation

## Calculate peptide correlation between and within peptides of one protein

### Description

Calculate peptide correlation between and within peptides of one protein

### Usage

    calculate_peptide_corr_distr(
      data_matrix,
      peptide_annotation,
      protein_col = "ProteinName",
      feature_id_col = "peptide_group_label"
    )

### 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")`)
`peptide_annotation` | long format data frame with peptide ID and their corresponding protein and/or gene annotations. See `help("example_peptide_annotation")`.
`protein_col` | column where protein names are specified
`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.

### Value

dataframe with peptide correlation coefficients that are suggested to use for plotting in `plot_peptide_corr_distribution` as `plot_param`:

### Examples

    selected_genes = c('BOVINE_A1ag','BOVINE_FetuinB','Cyfip1')
    gene_filter = example_peptide_annotation$Gene %in% selected_genes
    peptides_ann = example_peptide_annotation$peptide_group_label
    selected_peptides = peptides_ann[gene_filter]
    matrix_test = example_proteome_matrix[selected_peptides,]
    pep_annotation_sel = example_peptide_annotation[gene_filter, ]
    corr_distribution = calculate_peptide_corr_distr(matrix_test,
    pep_annotation_sel, protein_col = 'Gene')

[Package proBatch version 1.11.0 Index]