Projects

Mapping of phenotype descriptions in the OpenGWAS database to ontologies

Mapping of phenotype descriptions in 23andMe’s GWAS metadata to ontologies

Make MERFISH datasets accessible to the wider R/Bioconductor community.

Survey of tools for ontology mapping and benchmark test of mapping accuracy

Development of tool to programmatically interact with the HuBMAP ontology and to facilitate HuBMAP-based annotation tasks

Integrating candidate cis-regulatory elements from ENCODE, open chromatin regions from ATACdb, and super enhancers from SEdb into a machine learning framework for cancer immunotherapy

Create a Docker Image

Leverage a GIS database-backend to address big data problems in spatial transcriptomics

CCB works with the Farhat lab on a large-scale whole-genome sequencing (WGS) analysis of fluoroquinolone resistance (FQ-R) acquisition in Mycobacterium tuberculosis. This will involve (1) processing of WGS data of 32k genetically diverse M. tuberculosis genomes, (2) reconstructing phylogenetic models that relate diverse strains based on their genome sequences, and (3) identifying key mutations that have contributed to FQ-R emergence and spread.

CCB works with the Kagan lab on a single-cell study of COVID as part of a collaboration between HMS and AbbVie. The Kagan lab will also provide information on a panel of cytokines that were quantified on the protein level, sequencing data for T-cell receptors, as well as a variety of phenotypic and clinical characteristics of the participants. CCB will develop additional visualization components for interactive exploration of the analytic components of the project.

Build a relational database to catalog and track ~5000 transgenic or mutant C. elegans strains.

Implement programmatic access to BioPlex from within R/Bioconductor and from within Python, along with a series of downstream applications of BioPlex,

Developed an O2-based RNA-seq pipeline that enabled efficient processing of raw sequencing output for 500 samples.

Development of ontology mapping tool components—UIs for interactive mapping; integration of embedding models; and test harness for continuous QA

Developing a pair of modules on the O2 HPC cluster to facilitate protein structure prediction