SP 3

Integrative analysis to infer mutations and pathways causal for the disease    

In this project of the mitOmics junior group, we will infer causal mutations and causal pathways by integrating genotype, observational omics and genome-wide perturbation assays performed on patient-derived cell lines. Specifically, we propose to develop and apply algorithms for:

  • (1) Identifying causal mutations and pathways of individual patients. We will develop causal inference methods that infer causal pathways from genotype, gene expression and phenotypic data. Validations of our predictions will be performed by our experimental collaborators.

  • (2) Statistical analysis of pooled shRNA screens in patient-derived cell lines. We will establish a statistical analysis pipeline to robustly estimate condition- and patient-specific effects of pooled shRNA screens.
Genotype-Environment Interactions Reveal Causal Pathways That Mediate Genetic Effects on Phenotype (Gagneur et al. 2013) A) Genetic variants affect physiological phenotype through a causal chain of molecular events affecting expression of genes (nodes). Genes like A and B that mediate the effect of genetic variation on phenotype are valuable molecular intervention points to counteract genetic defects that cause aberrant phenotypes. B) Performance of our Bayesian network exploiting genotype-environment interactions (purple) in predicting causal intermediates vs. former method (pink).