Hub genes prediction for chronic obstructive pulmonary disease using mRNA expression data

Abstract

At the moment, chronic obstructive pulmonary disease (COPD) has a world-wide high death rate. And most of the deaths occur in low and middle income countries (LMICs). As the number of COPD patients increases every year, it is considered as a burden to the world. In the absence of a proper cure, we can just slow down the progression with medicines. Therefore researches need to be done in the direction of finding a cure for COPD. We have some positive results in this direction but more studies need to be done. We collect some mRNA expression data of a mouse to study the genes that are responsible for the disease. Our data has some control samples and some Disease samples. Our study was on the over expressed (up-regulated) genes to identify possible hub genes of COPD. We perform our task on python and Cytoscape. We cluster the data in some subgroups in python and then find the hub genes with the help of Cytoscape. For functional enrichment analysis like Gene Ontology (GO) and KEGG pathways we use Enrichr and DAVID. From the clusters we got 80 top ranked genes with the help of cytoHubba plugin in cytoscape by applying cytoHubba on every individual cluster. Then from the outcome we mark Rac2, Anxa5, Exosc10, Hif1a, Pik3r2, Tia1, Ctnnb1, Jak2, Bdnf, and Pten as the final 10 possible hub genes.