Craig Smail

The paper introduces a data model and dataset for rare disease research, enabling interoperable multi-omic data integration across clinical sites.

The paper expands the human genomic imprinting map using long-read sequencing and GWAS integration, revealing new disease-associated loci and maternal/paternal imprinting patterns.

This study quantifies polygenic liability in rare disease probands and finds associations between rare disease phenotypes and polygenic scores, supporting complex trait influences on Mendelian variant interpretation.

The paper uses long-read whole genome sequencing and polygenic scores to identify structural variants linked to rare diseases and prioritize candidate genes for functional validation.

This study integrates rare large-effect expression variants into polygenic risk scores, showing improved prediction of complex traits by including these variants in risk assessment.

The paper presents diagnostic analyses of 960 pediatric rare disease families using genomic sequencing and machine learning, finding higher diagnostic rates with long-read sequencing and highlighting challenges in variant interpretation.

The paper assesses NMD efficiency for PTVs across tissues and individuals, finding high concordance and demonstrating in silico prediction using peripheral tissues.

The paper maps regulatory effects of human disease variants in pluripotent cells, identifying cis- and trans-QTL across 18,556 genes and linking them to GWAS traits.

Integrating expression, allelic expression and splicing across tissues identifies rare variants with relevance to traits.

The paper examines how structural variants and short tandem repeats affect gene expression and complex traits, identifying high-impact variants associated with multiple genes and GWAS traits.

The paper discovers and genotypes a comprehensive set of structural variants and short tandem repeats using multiple algorithms and replicates, creating a well-characterized map of these variants.

This study evaluates the use of whole blood transcriptome sequencing for diagnosing rare diseases, finding an 8.5% diagnostic rate across 56 undiagnosed cases.