Research programs

Research

Di Genoma Lab develops computational genomics around cancer biology, long-read sequencing, human genetic diversity, and microbial multi-omics systems.

Core areas

Four connected research programs

The lab is organized around biological questions that require method development, sequencing, computation, and interpretation to be designed together rather than treated as separate steps.

01

Cancer genomics

We study structural variation, copy-number change, ecDNA, fusion discovery, ancestry-aware tumor biology, and multi-omic states in clinically relevant Chilean cancers.

Somatic SV Copy number Precision oncology Tumor heterogeneity
02

Long-read genomics and genome assembly

We build and apply long-read and hybrid methods for genome assembly, phasing, reference construction, and the interpretation of difficult genomic regions.

Nanopore Hybrid assembly Phasing Reference genomes
03

Human genetics and population genomics

We analyze Chilean and Latin American genomic diversity to improve ancestry-aware interpretation, disease association, and clinically relevant representation in genomics.

Admixed populations Human genetics Genetic ancestry Clinical relevance
04

Microbial and multi-omics systems

We work on metagenomics, metatranscriptomics, microbial adaptation, and multi-omics integration across environmental and disease-associated communities.

Metagenomics MOFA Microbial adaptation Systems biology
How we work

Research is built as an integrated stack

Across all programs, the lab combines sequencing strategy, laboratory coordination, high-performance computing, software development, and statistical interpretation inside one workflow.

Data generation

We design projects around the right assay, coverage profile, and sequencing platform instead of adapting methods after the fact.

Computation

We build portable pipelines and analysis environments that run reproducibly on local institutional infrastructure and HPC systems.

Interpretation

We connect genomic signals to tumor biology, population structure, microbial ecology, and translational questions that matter to collaborators.