Michael J. Cormier

Annotation of structural variants with reported allele frequencies and related metrics from multiple datasets using SVAFotate

SVAFotate annotates structural variants with allele frequency data from multiple datasets to help classify them as common or rare, aiding in rare disease analysis.

Combining genetic constraint with predictions of alternative splicing to prioritize deleterious splicing in rare disease studies

This paper introduces ConSpliceML, a machine learning model that improves the identification of deleterious splicing variants by integrating genetic constraint and alternative splicing predictions.

Samplot: A Platform for Structural Variant Visual Validation and Automated Filtering

Samplot creates visualizations for structural variant validation and includes a machine learning tool to reduce false positives across multiple sequencing technologies.

Go Get Data (GGD): simple, reproducible access to scientific data

GGD provides a fast, reproducible way to install standardized data recipes for genomics research, addressing challenges in data collection, transformation, and integration.