A Bayesian active learning platform for scalable combination drug screens.

Large-scale combination drug screens are generally considered intractable due to the immense number of possible combinations. Existing approaches use ad hoc fixed experimental designs then train machine learning models to impute unobserved combinations. Here we propose BATCHIE, an orthogonal approach that conducts experiments dynamically in batches.

BayesTME: An end-to-end method for multiscale spatial transcriptional profiling of the tissue microenvironment.

Spatial variation in cellular phenotypes underlies heterogeneity in immune recognition and response to therapy in cancer and many other diseases. Spatial transcriptomics holds the potential to quantify such variation, but existing analysis methods are limited by their focus on individual tasks such as spot deconvolution. We present BayesTME, an end-to-end Bayesian method for analyzing spatial transcriptomics data.

An eQTL mapping approach reveals that rare variants in the SEMA5A regulatory network impact autism risk.

To date, genome-wide single nucleotide polymorphism (SNP) and copy number variant (CNV) association studies of autism spectrum disorders (ASDs) have led to promising signals but not to easily interpretable or translatable results. Our own genome-wide association study (GWAS) showed significant association to an intergenic SNP near Semaphorin 5A (SEMA5A) and provided evidence for reduced expression of the same gene. In a novel GWAS follow-up approach, we map an expression regulatory pathway for a GWAS candidate gene, SEMA5A, in silico by using population expression and genotype data sets.

Acute and posttraumatic stress symptoms in a prospective gene x environment study of a university campus shooting.

Context: The serotonin transporter (SLC6A4) has been associated with several stress-related syndromes including posttraumatic stress disorder (PTSD). The ability to detect meaningful associations is largely dependent on reliable measures of preexisting trauma.

Objective: To study the association of genetic variants within SLC6A4 with acute and posttraumatic stress symptoms in a civilian cohort with known levels of preexisting trauma and PTSD symptoms collected prior to a shared index traumatic event.