Large-scale integration to renewable energy in the power system promotes the energy structure optimization，while at the same time，it brings uncertainties to the power system operation. In order to improve the stability of power systems with renewable energy integration，it is necessary to study the power system analysis method considering uncertainties，and identify the key uncertainties which have large impacts on the small signal stability of power systems accurately and quickly. This paper focuses on the small signal stability of power systems in the background of large-scale integration to renewable energy. A small signal stability model with wind power integration is established and three sensitivity analysis methods，including the one-at-a-time method，the trajectory method and the global method are compared to determine the key uncertainty in the eigenvalue of the status matrix. In addition，the sparse polynomial chaos expansion （SPCE） method is used to improve the efficiency of the global sensitivity analysis. A 14-bus system is used to test the accuracy and efficiency of sensitivity analysis methods mentioned in this paper，and the effectiveness of the global sensitivity analysis method is verified.