Olympia oysters, Ostrea lurida, are currently the subject of multiple restoration projects along the west coast of the United States due to threats from historical overharvesting and habitat degradation, including restoration at Upper Newport Bay. Typical metrics of restoration success are focused on organismal health metrics such as growth and survival, but do not directly address sub lethal or chronic effects of stressors such as contaminants. This study performed whole transcriptome sequencing on O. lurida oysters that were previously analyzed for organic and trace metal contaminant analysis and were collected from four restoration sites at Upper Newport Bay with variable restoration techniques. Differential gene expression and functional analysis were used to evaluate differences between the oysters from various sites, plots with different restoration techniques, and between oysters held in a laboratory versus collected in the field. Finally, artificial neural networks were used to compare the oyster' molecular profile with environmental variables, including previously determined contaminant concentrations.