Cancer Transcriptome Analysis with RNA-Seq Using Quantum K-means Clustering Algorithm

A quantified RNA transcriptome is of particular interest in biomedical research as it can be for cancer diagnosis. Quantum algorithms can give exponential performance gains over their classical counterparts. In this paper, we implement a quantum clustering technique to classify the cells into different cancer types. To verify our implementation, we test it using the standard ‘gene expression cancer RNA-Seq’ dataset. The experimental results show that our algorithm achieves high accuracy of 94.8% (on average) in classifying the different types of cancer.