I am a genomics data scientist with extensive expertise in the analysis of next-generation sequencing data sets, including WGS, Exome-seq, RNA-seq, ATAC-seq and Pacbio long read SMRT-seq. I joined the Jackson Laboratory in 2016 to help developing a groundbreaking research program aimed at the identification of cancer isoforms using long-read sequencing. Our premise is that splicing aberration in cancer generates RNA-based tumor antigens that can be exploited for immunotherapy.
Using Machine Learning, Genomics and Proteomics, we are characterizing the landscape of RNA alterations in breast cancer, melanomas, lung and ovarian cancers. I am also a Software Carpentry instructor teaching R, Bioconductor and Genomics to scientists at JAX.
The full description of my research activities is available on https://diogoveiga.github.io/