NeighborNetwork_Clustering: Neighbor network clustering analysis.

In masato-ogishi/Repitope: Epitope immunogenicity prediction through in silico TCR-peptide contact potential profiling

Neighbor network clustering analysis.

Description

neighborNetwork_ConnectedSubGraph and neighborNetwork_ConnectedSubGraphDF extract the minimum connected subgraph focusing on a target peptide.
neighborNetwork_Cluster and neighborNetwork_Cluster_Batch conduct a network clustering analysis using a walktrap algorithm.
neighborNetwork_Cluster_FeatureDF computes per-cluster and per-peptide features, including "escape potential".

Usage

neighborNetwork_ConnectedSubGraphDF(neighborNetResult, peptide)

neighborNetwork_ConnectedSubGraph(neighborNetResult, peptide)

neighborNetwork_Cluster(peptide, graph, metadataDF, seed = 12345, plot = T)

neighborNetwork_Cluster_Batch(
  neighborNetResult,
  metadataDF,
  seed = 12345,
  coreN = parallel::detectCores(logical = F)
)

neighborNetwork_Cluster_FeatureDF(
  neighborNetClusterResult,
  coreN = parallel::detectCores(logical = F)
)

Arguments

neighborNetResult	The result returned from neighborNetwork.
peptide	A target peptide sequence.
graph	A directed and weighted neighbor network of the target peptide.
metadataDF	A dataframe which has "Peptide" and "ImmunogenicityScore" columns. Optionally, an "Immunogenicity" column would be integrated if present.
seed	A random seed.
plot	Logical. Whether the network cluster plot shuould be generated.
coreN	The number of threads for parallelization.
neighborNetClusterResult	The result returned from neighborNetwork_Cluster_Batch.

masato-ogishi/Repitope documentation built on Feb. 14, 2023, 5:47 a.m.