Multiple testing becomes an increasingly important topic in high-dimensional statistical analysis. However, most commonly used false discovery rate estimation and control methods do not take covariates into consideration. To better estimate false discovery rate, we propose a novel nonparametric method which efficiently utilizes the covariate information. Our proposed method enjoys some desirable theoretical properties. In addition, we evaluate the performance of our proposed method over existing methods using simulation studies.