Cohort-scale analysis, gene discovery, diagnostic sequencing, and phenotype expansion.
Clinical Genomic Scientist II · Human genomics / rare disease
E. Andrés
Rivera-Muñoz, PhD
I use large-scale genomic data, computational methods, and clinical interpretation to understand rare disease—and improve how we move from variants to diagnoses.
01 / FOCUS
Science at the boundary of data and diagnosis.
Variant interpretation, mosaicism, long reads, reanalysis, and pipeline development.
Using large clinical datasets to strengthen discovery and improve diagnosis.
02 / ABOUTFrom biological questions
From biological questions
to usable evidence.
My work follows a consistent question: how can we make genomic evidence more useful for people with rare and undiagnosed disease?
I am a Clinical Genomic Scientist II at a clinical diagnostics laboratory, where I interpret and classify variants from clinical diagnostic testing and translate genomic and clinical evidence into clear reports. My path—from biology and human genetics through computational genomics and clinical sequencing—has shaped a translational view of discovery.
I earned my PhD in Genetics and Genomics at Baylor College of Medicine, after research training at the University of Chicago and a BS in Biology from UNC–Chapel Hill. I work in Spanish and English and have intermediate German proficiency.
- Biology
- Human genetics
- Computational genomics
- Clinical interpretation
03 / RESEARCHQuestions worth
Questions worth
following deeply.
Selected research stories, organized around the problem—not the chronology.
01
Rethinking genetic testing for congenital kidney disease
Clinical exomes · cohort genomics · phenotype expansion
- Problem
- Congenital anomalies of the kidney and urinary tract are clinically common but genetically heterogeneous.
- Gap
- Narrow panels and phenotype-first testing can leave relevant diagnoses behind.
- Approach
- Evaluate cohort-scale clinical exome data across a broad, phenotypically diverse population.
- Impact
- A clearer view of diagnostic yield, genetic architecture, and the value of broad sequencing.
02
Finding mosaic variants hiding in routine genomes
Somatic mosaicism · rare disease · validation
- Problem
- Disease-causing variants may be present in only a fraction of a patient’s cells.
- Gap
- Standard germline workflows can miss low-level mosaic signal in unsolved cases.
- Approach
- Reanalyze genome data with mosaic-aware calling, inheritance modeling, visual review, and orthogonal validation.
- Impact
- A practical route to recover clinically meaningful variation from data already in hand.
03
Learning from unsolved dysautonomia
POTS · exome sequencing · cohort design
- Problem
- Complex, heterogeneous phenotypes resist simple monogenic explanations.
- Gap
- Negative findings are often treated as endpoints rather than evidence about study design.
- Approach
- Interrogate candidate variation while examining phenotype definition, cohort structure, and power.
- Impact
- Sharper hypotheses—and better-designed studies—for the next generation of gene discovery.
04
Building better genomic interpretation systems
Long reads · RNA-seq · investigator tools
- Problem
- Rich sequencing assays generate evidence that is difficult to integrate and explore.
- Gap
- Researchers need interpretable workflows that connect variants, annotations, and biological context.
- Approach
- Build reproducible pipelines and investigator-facing interfaces across small, structural, and noncoding variation.
- Impact
- Faster, more transparent movement from raw data to testable biological insight.
04 / PUBLICATIONS + PRESENTATIONS
Selected scholarly work.
Peer-reviewed research, preprints, invited programming, and conference presentations across clinical genomics, rare disease, and computational genetics.
Performance Characteristics of Reasoning Large Language Models for Evidence Extraction from Clinical Genomics Literature
medRxiv · Co-author
Exome Sequencing Efficacy and Phenotypic Expansions Involving Congenital Anomalies of Kidney and Urinary Tract
European Journal of Human Genetics · First author
Improving Automated Deep Phenotyping Through Large Language Models Using Retrieval Augmented Generation
Genome Medicine · Co-author
GREGoR: Accelerating Genomics of Rare Disease
Nature Genetics · GREGoR Consortium
Considerations for reporting variants in novel candidate genes identified during clinical genomic testing
Genetics in Medicine · Co-author
Quantifying the potential of functional evidence to reclassify variants of uncertain significance
Human Mutation · Co-author
Selected presentations
From Data to Diagnosis: Advancing Rare Disease Research through Collaborative Genomics
American Society of Human Genetics · Boston
Analysis of potentially mosaic variation within GREGoR cohorts
SMaHT Consortium Annual Meeting · Washington, DC
Exome sequencing efficacy and phenotypic expansions involving congenital anomalies of kidney and urinary tract
American Society of Human Genetics · Washington, DC
Integrating Genomic and Phenotypic Analyses of Autonomic Nervous System Dysfunction in a Rare Disease Cohort
GREGoR · ASHG
05 / COMPUTATIONAL WORK
Tools are part of the science.
I build analysis workflows that make complex genomic evidence reproducible, inspectable, and useful to investigators.
Mosaic variant discovery
Variant calling → filtration → inheritance modeling → IGV review → orthogonal validation
Long-read interpretation
Integrated annotation of small, structural, and noncoding variation with an investigator-facing interface.
R · Python · Hail · DRAGEN · bcftools · VEP · Shiny · Streamlit · OpenCRAVAT · IGV
06 / CV + RESUME
A scientist who can move between the cohort, the command line, and the clinic.
PhD in Genetics and Genomics from Baylor College of Medicine, with experience spanning clinical diagnostics, cohort-scale rare disease research, ClinGen, GREGoR, and multi-omic analysis.
Selected professional highlights, scholarly work, and technical expertise are presented throughout this site.
Science is collaborative.
I value the communities that make rigorous science more open, connected, and humane.
My leadership has included engagement and outreach for STEM Pride of the Triangle, coordination across ClinGen expert panels and working groups, and standards, policy, and variant-to-function work within GREGoR.
Have a hard genomic question?
Let’s talk about rare disease, clinical sequencing, computational genomics, collaboration, or scientific roles.
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