1. SuShiE (Sum of Shared single Effects) is a Python software to fine-map multi-ancestry molecular QTL data. The software takes as input genotype data (e.g., PLINK, VCF, etc) along with transcriptomic phenotypes (e.g., BED file) and outputs for each gene, posterior inclusion probabilities (i.e. PIPs) and credible sets of genetic variants shared across ancestries, ancestry-specific prediction weights for FUSION TWAS, and inferred correlations of molQTL effect sizes across multiple ancestries.

  2. SuSiE-PCA (Sum of Single Effects, Principal Components Analysis) is a Python software for an efficient variable selection in PCA when dealing with high dimensional data with sparsity, and for quantifying uncertainty of contributing features for each latent component through posterior inclusion probabilities (PIPs). The model extends the Sum of Single Effects (i.e. SuSiE) model to principal components analysis.

  3. FactorGo (Factor analysis model of Genetic assOciations) is a scalable variational factor analysis model that learns pleiotropic factors from GWAS summary statistics. The software takes as input summary GWAS data from multiple traits/diseases and outputs estimated latent factors for each phenotype, as well as loadings (i.e. effect-sizes) for each variant along the latent dimensions.

  4. HAMSTA (Heritability estimation from Admixture Mapping Summary STAtistics) is a Python software to estimate heritability explained by local ancestry data from admixture mapping summary statistics. It also quantifies inflation in test statistics that is not contributed by local ancestry effects, and determines a genome-wide significance threshold for admixture mapping studies.

  5. MA-FOCUS (Multi-ancestry Fine-mapping Of CaUsal gene Sets) is software to fine-map multi-ancestry transcriptome-wide association study statistics at shared genomic risk regions. The software takes as input summary GWAS data along with eQTL weights for each ancestry group and outputs a credible set of genes to explain observed genomic risk.

  6. TWAS Simulator is software to simulate a complex trait as a function of latent steady-state expression, fit eQTL weights in independent data, and perform GWAS+TWAS on the simulated complex trait.

  7. FOCUS (Fine-mapping Of CaUsal gene Sets) is software to fine-map transcriptome-wide association study statistics at genomic risk regions. The software takes as input summary GWAS data along with eQTL weights and outputs a credible set of genes to explain observed genomic risk.

  8. FIZI (Functionally-Informed Z-score Imputation) leverages functional information together with reference linkage-disequilibrium (LD) to impute GWAS summary statistics (Z-scores).

  9. RHOGE is an R package that estimates the genome-wide genetic correlation between two complex traits (diseases) as a function of predicted gene expression effect on trait (ρge). Given output from two transcriptome-wide association studies, RHOGE estimates the mediating effect of predicted gene expression and estimates the correlation of effect sizes across traits (diseases). This approach is extended to a bi-directional regression that provides putative causal directions between traits with non-zero ρge.

The banner image was taken at Vazquez Rocks in Winter 2019.