GMRC: Gene Median Ratio Clustering Algorithm to Rank Clusters and Identify Driver Genes in Intrahepatic Cholangiocarcinoma

Abstract

AbstractIntrahepatic Cholangiocarcinoma (iCCA) is an asymptomatic malignancy of the bile ducts in the liver. The research is predicated on the assumption that a disease is a cluster of genes interacting in a regulatory network and a few driver genes regulating the network. Keeping this in mind, the paper proposes a Gene Median Ratio Clustering (GMRC) algorithm to independently rank the clusters and identify driver genes by hybridizinggene-median ratio(GMR) andgene cluster network(GCN). GMR then employs the Poisson distribution to translate right-skewed data into the Normal distribution and the Anscombe transformation to eliminate data noise and determine the median difference in gene concentration between distinct disease stages. Additionally, hierarchical clustering is separately applied to raw data for gene clustering based on the RNA sequence count. In the process, GMRC is evaluated over the GSE32225 dataset of 155 patients to extract 12 clusters network for proliferation patients.