With the rapid development of quantum computers, researchers have shown quantum advantages in physics-oriented problems. Quantum algorithms tackling computational biology problems are still lacking. In this talk, I will demonstrate the quantum advantage in analyzing single-cell omics data.  I will present a quantum algorithm that takes advantage of quantum parallelism by integrating binary search and Grover's algorithm to enable fast computation. Theoretical results are provided to show the privilege of the algorithm in the estimation error and computational complexity. The empirical performance of the algorithm is demonstrated on both the IBM quantum computer and simulator.