The research focus of the Functional Genomics group led by Robert Castelo is the development of statistical and computational methods and pipelines for the analysis and comprehension of high-throughput genetics and genomics data, motivated by questions of biological and clinical relevance.
Research lines
- Reverse engineering the genotype-phenotype map
Genes and molecules are activated in a coordinated manner under finely tuned regulatory programs. High-throughput genetics and genomics data offer a unique opportunity to witness this phenomenon by monitoring the simultaneous action of thousands of genes and millions of genotypes. We try to embrace this complexity by developing computational tools that enable estimating multivariate statistical models from these data, which have the potential to disentangle direct from indirect or spurious effects.
- Variant annotation and filtration
The increased number of individuals profiled by genomics technologies steadily uncovers an increasing number of cases in which pathogenic mechanisms work conditionally on the cellular context where genetic alterations take place, hindering the interpretation of individual mutations. In collaboration with clinical geneticists, we are trying to approach this problem by developing novel methodologies for the annotation and filtration of genetic variants.
- Prematurity and fetal immunity
Intrauterine inflammation and infection increase the risk for perinatal mortality and morbidity and its frequency increases with lower gestational age at birth. In collaboration with pediatricians and obstetricians, we study the transcriptome and proteome of extremely preterm newborns (< 28 weeks of gestational age) to try to understand the extent of molecular changes that participate in the fetal inflammatory response to an intrauterine infection and how these changes lead to adverse neonatal outcome.
Website of group: https://functionalgenomics.upf.edu/index.html