wppi: The wppi package

In AnaGalhoz37/wppi: Weighting protein-protein interactions

The wppi package

Description

The wppi package calculates context specific scores for genes in the network neighborhood of genes of interest. The context specificity is ensured by the selection of the genes of interest and potentially by using a more relevant subset of the ontology annotations, e.g. selecting only the diabetes related categories. The PPI network and the functional annotations are obtained automatically from public databases, though it's possible to use custom databases. The network is limited to a neighborhood of the genes of interest. The ontology annotations are also filtered to the genes in this subnetwork. Then the adjacency matrix is weighted according to the number of common neighbors and the similarity in functional annotations of each pair of interacting proteins. On this weighted adjacency matrix a random walk with restart is performed. The final score for the genes in the neighborhood is the sum of their scores (probabilities to be visited) in the random walk. The method can be fine tuned by setting the neighborhood range, the restart probability of the random walk and the threshold for the random walk.

Author(s)

Ana Galhoz [e-mail] and Denes Turei [e-mail]

Examples

# Example with a single call:
genes_interest <-
    c("ERCC8", "AKT3", "NOL3", "GFI1B", "CDC25A", "TPX2", "SHE")
scores <- score_candidate_genes_from_PPI(genes_interest)
# The workflow step by step:
db <- wppi_data()
genes_interest <-
    c("ERCC8", "AKT3", "NOL3", "GFI1B", "CDC25A", "TPX2", "SHE")
graph_op <- graph_from_op(db$omnipath)
graph_op_1 <- subgraph_op(graph_op, genes_interest, 1)
w_adj <- weighted_adj(graph_op_1, db$go, db$hpo)
w_rw <- random_walk(w_adj)
scores <- prioritization_genes(graph_op_1, w_rw, genes_interest)

AnaGalhoz37/wppi documentation built on Nov. 8, 2022, 7:47 a.m.