cc_stats {net4pg}

Provide statistics on the CCs size

Description

Provides the CC size distribution, which is the number of CCs including a given number of protein members, and the proportion of single- vs multi-protein CCs.

Usage

cc_stats(incM, cc.proteins, reducedIncM)

Arguments

incM

a logical matrix containing the incidence matrix with its column and row names (respectively, protein and peptide identifiers) names and 0 or 1 values indicating whether or not the peptide maps on the corresponding protein.

cc.proteins

a list of vectors (one for each connected component), each enumerating the proteins members of a connected component.

reducedIncM

a logical value indicating if the input matrix is the original complete incidence matrix or a reduced version of it which only contains proteins with at least one shared peptide and all peptides mapping on such proteins (generated by the reduce_inc_matrix function.

Value

a list of four outputs: i. a vector containing all those proteins which belong to single-protein connected component (each protein is a single-protein connected component); ii. an integer representing the number of single-protein CCs; iii. an integer representing the number of multi-protein CCs; iv. a data.frame describing size distribution of connected components (number of connected components per number of protein members)

Author(s)

Laura Fancello

Examples

# Read the tab-delimited file containing he proteome incidence matrix
incM_filename <- system.file("extdata"
                             , "incM_example"
                             , package = "net4pg"
                             , mustWork = TRUE)
rownames_filename <- system.file("extdata"
                                  , "peptideIDs_incM_example"
                                  , package = "net4pg"
                                  , mustWork = TRUE)
colnames_filename <- system.file("extdata"
                                 , "proteinIDs_incM_example"
                                 , package = "net4pg"
                                 , mustWork = TRUE)
incM <- read_inc_matrix(incM_filename = incM_filename
                 , colnames_filename = colnames_filename
                 , rownames_filename = rownames_filename)
# Only retain proteins with at least one shared peptide and all peptides
# mapping on such proteins.
incM_reduced <- reduce_inc_matrix(incM)
# Generate adjacency matrix describing protein-to-protein mappings
adjM <- get_adj_matrix(incM_reduced)
# Generate graph of protein-to-protein connections and calculate its
# connected components
multProteinCC <- get_cc(adjM)
# CCs size and percentage of single-vs multi-protein CCs
CCstatsOut <- cc_stats(incM = incM_reduced
                      , cc.proteins = multProteinCC$ccs
                      , reducedIncM = TRUE)