calculate_peptide_corr_distr {proBatch} | R Documentation |
Calculate peptide correlation between and within peptides of one protein
calculate_peptide_corr_distr( data_matrix, peptide_annotation, protein_col = "ProteinName", feature_id_col = "peptide_group_label" )
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 |
peptide_annotation |
long format data frame with peptide ID and their
corresponding protein and/or gene annotations.
See |
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 |
dataframe with peptide correlation coefficients
that are suggested to use for plotting in
plot_peptide_corr_distribution
as plot_param
:
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')