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Generates a detailed functional profile of a musculoskeletal community by combining network topology metrics with knowledge graph annotations. This enables characterization of communities by their anatomical region, innervation patterns, primary actions, and spinal segment involvement.

Usage

mskCommunityProfile(hg = NULL, community_id, hub = NULL, gamma = 4.3)

Arguments

hg

An MSKHypergraph object. If NULL, loads default network.

community_id

Integer, the community to profile (1-based).

hub

A PhysioAnnotationHub object (NULL loads default).

gamma

Numeric, resolution parameter for community detection (default: 4.3, as in Murphy et al. 2018).

Value

An S3 object of class "MSKCommunityProfile" with:

community_id

Integer, the profiled community

muscles

Character vector of muscle names in the community

n_muscles

Integer, number of muscles

action_profile

Table of primary action distribution

nerve_profile

Table of innervating nerves distribution

region_profile

Table of body region distribution

spinal_profile

Table of spinal level distribution

dominant_action

Most frequent primary action

dominant_nerve

Most frequent innervating nerve

dominant_region

Most frequent body region

mean_degree

Mean hyperedge degree of community muscles

mean_impact_deviation

Mean impact deviation score

Clinical Validity

Community membership depends on the resolution parameter gamma and the stochastic Louvain algorithm. Profile annotations depend on KG completeness. Community boundaries are network-derived, not anatomical boundaries.

References

Murphy AC et al. (2018) PLOS Biology 16(1): e2002811.

Examples

if (FALSE) { # \dontrun{
profile <- mskCommunityProfile(community_id = 1)
print(profile)
} # }