HDBIG

Recent advances in brain imaging and high throughput genotyping and sequencing techniques enable new approaches to study the influence of genetic variation on brain structure and function. HDBIG is a collection of software tools for high dimensional brain imaging genomics. These tools are designed to perform comprehensive joint analysis of heterogeneous imaging genomics data.

Tools

HDBIG-SR: An HDBIG toolkit for sparse regression with a few regularization terms, including lasso, elastic net, L21 norm, group L21 norm, and network guided L21 norm.

HDBIG-SCCA: An HDBIG toolkit for sparse association discovery with a knowledge-guided regularization term.

HDBIG-S2CCA: An HDBIG toolkit for structured sparse association discovery with a few Sparse Canonical Correlation Analysis (SCCA) models, including the structure-aware SCCA model (S2CCA), the GraphNet SCCA model (GN-SCCA), the Graph OSCAR SCCA (GOSC-SCCA) model, and the Absolute value based GraphNet SCCA model (AGN-SCCA).

HDBIG-SCCA-NC: An HDBIG toolkit for structured sparse association discovery with a generic non-convex penalty.

HDBIG-S2CCA-TLP: An HDBIG toolkit for structured sparse association discovery with a truncated l1-norm penalty.

HDBIG-IGEA: An HDBIG toolkit for mining high-level imaging genetic associations via applying enrichment analysis to two dimensional imaging genetic modules.

HDBIG-NWAS-RP: An HDBIG toolkit for mining high-level imaging genetic associations using tissue-specific functional networks and network GWAS reprioritization strategy.

HDBIG-IGB-W: An HDBIG web interface for archiving, visualization and interactive exploration of brain imaging genetics findings.