SOLAR-eclipse

SOLAR-eclipse performs genetic variance-components and association analyses to quantify heritability and detect linkage and SNP association signals (including QTN and QTLD) for neuroimaging phenotypes to study genetic influences on brain connectivity.

Key Features:

• Imaging genetics integration: Handles neuroimaging-derived measures including diffusion tensor imaging (DTI) and computes metrics such as fractional anisotropy (FA).
• Variance-components analysis: Implements genetic variance-components methods to partition phenotypic variance into genetic and environmental components.
• Linkage analysis: Performs linkage analysis to localize genomic regions contributing to neuroimaging traits.
• Quantitative genetic analysis: Conducts quantitative genetic analyses for continuous neuroimaging phenotypes.
• SNP association analysis (QTN and QTLD): Supports single nucleotide polymorphism association testing including QTN and QTLD approaches.
• Covariate screening: Incorporates covariate screening to control for non-genetic influences on neuroimaging measures.
• Heritability estimation: Calculates heritability estimates for measures such as FA across major white matter tracts in cohorts like the Human Connectome Project (HCP).
• Comparative analysis with ENIGMA-DTI: Enables comparison of heritability estimates against ENIGMA-DTI pooled estimates from multiple family-based studies.
• Cross-population consistency assessment: Assesses correlation of heritability estimates between HCP and ENIGMA cohorts at tract and voxel levels to evaluate consistency across populations and imaging parameters.
• Gene-discovery facilitation: Identifies a common genetic search space to prioritize loci for future gene-discovery studies of brain connectivity.

Scientific Applications:

• Mapping genetic architecture of brain connectivity: Quantifies genetic contributions to connectivity and white matter structure using DTI-derived measures such as FA.
• Large-scale cohort analysis: Applied to cohorts like the Human Connectome Project (HCP) for family-based heritability and association studies.
• Cross-study comparisons: Facilitates comparison of imaging genetics results with aggregated consortium data such as ENIGMA-DTI.
• Variant prioritization for neuroimaging phenotypes: Supports identification and prioritization of SNPs and linkage regions associated with neuroimaging traits.

Methodology:

Integrates neuroimaging and genetic data and applies heritability estimation, variance-components and linkage analyses, SNP association tests (QTN, QTLD), and covariate screening.