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Core Functions

The primary interface for running bHIVE algorithms. Use bHIVE() for single-pass analysis, honeycombHIVE() for multilayer hierarchical refinement, and refineB() for gradient-based post-processing.

bHIVE()
bHIVE: B-cell Hybrid Immune Variant Engine
honeycombHIVE()
honeycombHIVE: Multilayer AIS with optional gradient-based fine-tuning
refineB()
refineB: Gradient-based fine-tuning for bHIVE antibodies with multiple loss functions and optimizers
visualizeHIVE()
Visualize bHIVE/honeycombHIVE Results

Bioconductor Integration

Run bHIVE through bluster::clusterRows() and bluster::clusterSweep(). bHIVE() also accepts SummarizedExperiment and SingleCellExperiment objects directly.

Hyperparameter Tuning

Grid search over bHIVE hyperparameters with BiocParallel support.

swarmbHIVE()
Tune Hyperparameters for bHIVE (Swarm/Grid Search)

R6 Algorithm Classes

Object-oriented interface for composing immune algorithms with injectable modules. AINet is the primary class; ImmuneAlgorithm is the abstract base.

AINet
AINet
ImmuneAlgorithm
ImmuneAlgorithm
ImmuneRepertoire
ImmuneRepertoire

Mutation & Selection Modules

Modules controlling how antibodies mutate, compete, and are selected. Inject these into AINet$new() to customize algorithm behavior.

SHMEngine
SHMEngine
GerminalCenter
GerminalCenter
VDJLibrary
VDJLibrary

Network Regulation Modules

Modules for repertoire regulation and activation control.

IdiotypicNetwork
IdiotypicNetwork
ActivationGate
ActivationGate

Adaptation & Memory Modules

Modules for environment-driven adaptation, memory, and ensemble methods.

Microenvironment
Microenvironment
MemoryPool
MemoryPool
ClassSwitcher
ClassSwitcher
ConvergentSelector
ConvergentSelector

caret Integration

Model objects for use with the caret package’s train() function.

bHIVEmodel
bHIVE classification model for caret
honeycombHIVEmodel
Multilayered honeycombHIVE classification model for caret