Software

BSTD

Link stationary and time-varying functional connectivity to cognition, with posterior summaries of predictive edges, brain regions, and temporal patterns.

LatentSNA

Jointly model brain connectivity and behavioral measurements through a latent space framework.

SF Gradient Coupling

Construct and analyze structural–functional gradient coupling, including behavioral and genetic associations.

SBP

Construct brain nodes and networks using voxel-level imaging and a behavioral outcome.

ABCModel

Estimate group-level structural or functional connectivity jointly with regional attributes through a latent space model.

HyBRiD

Learn relationships among groups of brain regions and use the resulting representations for cognitive outcome prediction.

GenCPM

Predict continuous, binary, categorical, and time-to-event outcomes from brain connectivity, with optional non-imaging covariates and regularized regression.

COSR

Study spatially varying associations between brain shape and functional connectivity.

CoCR

Relate paired covariance structures through regression, with an R implementation and example script.

scMODAL

Align single-cell datasets across modalities with deep generative learning and feature links, supporting integrated representations and downstream analyses.

JNNT

Combine brain node and network predictors in a Bayesian thresholded model for outcome prediction and feature selection.

MMBeans

Identify subtypes and state-specific network modules by combining stochastic block models with Bayesian nonparametric clustering.

Nebula

Nonparametric Bayesian clustering of multi-view and multimodal data, using network structure to learn groupings.

BHPI

Estimate overlapping disease groups and risk-factor associations, with posterior uncertainty.

BNMM

Perform mediation analysis with a network-valued mediator.

Network mediation for survival

Estimate exposure–network and network–survival relationships jointly, with pathway summaries at the subnetwork and node levels.

BMZ-DP

Jointly model clustered recurrent events with zero inflation and a terminal event using Bayesian semiparametric inference.

CoSA

Integrate high-dimensional imaging and genetic features to predict time-to-event outcomes and identify discriminative features.

GIANT

Construct heritability-aware brain parcellations for imaging genetics; the repository provides atlas files, analysis code, and summary statistics.

NRSS

Estimate genetic associations with brain structural networks using structured shrinkage to identify affected connectivity patterns.

BNME

Model genetic associations with brain network phenotypes while accounting for relatedness and population structure through Bayesian mixed effects.

BANFF

An R package for gene network feature selection.

Biomarker trajectories before disease onset

Estimate biomarker trajectories on age and disease-onset time scales while accounting for delayed entry and right censoring.

BSSS

Jointly select imaging predictors and interactions across modalities using a prior that incorporates brain topology and the relationship between main and interaction effects.

BCHA

Identify subgroups with distinct brain–cognition relationships by jointly modeling multi-state functional connectomes, network features, and cognitive outcomes.