qpgraph

qpgraph is a software tool to tackle the complexities of mapping expression quantitative trait loci (eQTL) by addressing gene-expression traits' high-dimensional, multivariate nature. The software confronts the challenges posed by expression heterogeneity, which can arise from confounding factors, unwanted variation, and indirect effects that permeate through genes due to genetic, molecular, and environmental perturbations. qpgraph utilizes mixed graphical Markov models, higher-order conditional independences, and q-order correlation graphs to adjust for the effects of these factors, aiming to reveal a network of direct associations that trace the path from genotype to phenotype.

By leveraging these advanced statistical models, qpgraph demonstrates how additive genetic effects are propagated through the network as a function of gene-gene correlations. In analyzing a well-studied yeast dataset, qpgraph efficiently estimates the eQTL network, resulting in a sparse structure characterized by direct genetic and regulatory associations, facilitating a clear comparison of genetic control over gene expression across chromosomes. Notably, the analysis also uncovers that eQTLs account for a significant portion of the expression variability in network hub genes, indicating their pivotal role in gene regulation.