Adaptive immune response to West Nile virus infection in the Collaborative Cross mouse model: A database of cellular phenotypes and Quantitative Trait Loci

West Nile virus (WNV) infection can lead to a wide range of clinical outcomes, from asymptomatic to self-limiting febrile and serious neuro-invasive disease. Knowledge of the genetic factors contributing to the heterogeneity of this disease can inform pathogenic mechanisms, help guidethe development of cell based therapeutics, vaccines and inform lifestyle choices. Yet this knowledge is incomplete in humans. Here we present data from a large-scale experiment aimed at identifying quantitative trait loci (QTL) associated with adaptive immune cellular phenotypes observed in response to infection with WNV. This data was generated using the Collaborative Cross (CC) mouse model, previously demonstrated as a representative model for human WNV infection and homeostatic immune states. In addition, due to challenges of QTL mapping with the large number of intermediate, highly coordinated immune and virologic phenotypes, we also provide a computational pipeline for the prioritization of gene candidates designed to leverage those characteristics for downstream mechanistic studies.