Research

My research focuses on leveraging single-cell genomics, transcriptomics, and population genetics to understand human genetic diversity, cell-type-specific regulation, and complex traits across diverse populations.

Current Research Projects

Single-Cell Population Genomics

Focus: Single-cell RNA sequencing (scRNA-seq) analysis of Peripheral Blood Mononuclear Cells (PBMCs) from indigenous populations of Colombia.

  • Goal: Characterize cell-type-specific transcriptomic variation and immune diversity in underrepresented Latin American populations.
  • Methods: Pseudobulk aggregation, cell type annotation (Azimuth, MapMyCells), differential expression (edgeR, Seurat), and quality control workflows in R and Python.
  • Affiliation: MorenoLab (Cinvestav / LANGEBIO).

Human Brain & Neurogenomics

Focus: Single-cell and spatial transcriptomic workflows in human brain tissue to map neurodevelopmental patterns and cellular diversity.

  • Goal: Investigate cell-type specific gene expression changes in brain regions and their association with neurodevelopmental contexts.
  • Methods: High-throughput single-cell data processing, reproducible workflows, and cluster execution using Slurm HPC environments.
  • Affiliation: Lieber Institute for Brain Development.

Computational & Methodological Focus

  • Single-Cell Processing: Interoperability between R and Python environments (zellkonverter, SingleCellExperiment, AnnData).
  • High-Performance Computing: Scalable Slurm job scheduling, Conda environment management, and version control (git/GitHub) for genomic workflows.
  • Numerical Methods & Algorithms: Development of custom algorithmic solutions for numerical analysis and data transformation.