About Reomics

Built by people who know the scale of the problem.

Reomics grows from work on large public RNA-seq resources and a belief that better metadata is essential to turn those resources into usable evidence.

Our lineage

From recount to Reomics.

recount3 demonstrated uniform processing and access to expression and splicing summaries across a vast collection of public RNA-seq data. Members of the Reomics team contributed to the recount ecosystem and its research workflows.

Reomics is a new effort focused on the missing connective tissue: harmonized, validated metadata and prioritized evidence for biomedical and drug-development questions.

Reference: Wilks et al., “recount3: summaries and queries for large-scale RNA-seq expression and splicing,” Genome Biology (2021).

The team

Scientific depth. Practical execution.

The pitch deck describes a small technical team spanning RNA-seq analysis, engineering, and translational data science.

Leo Collado-Torres, PhD

RNA-seq analysis, recount2 co-lead, and recount3 package maintainer. Focused on metadata schema, Bioconductor access, and disease-cohort definitions.

Nicholas Eagles

Computational genomics and engineering across metadata pipelines, quality review, reproducible workflows, and processing pilots.

John Muschelli, PhD

Data science translation, infrastructure coordination, partner discovery, and translational reporting.

How we think

Useful science needs trustworthy context.

Our first priority is to build an auditable curation layer: clear source records, normalized labels, confidence measures, and a path for correction. It is the groundwork for future query and processing tools.

Work with Reomics

Let’s discuss what the data could answer.

We welcome conversations with biotechnology and pharmaceutical teams, researchers, and prospective collaborators.

Start a conversation