DETERMINATION OF MALIGNANT MELANOMA BY ANALYSIS OF VARIATION VALUES

Abstract

Melanoma is aserious disease associated withmutation-based cancer cells. Geneticstructure andhereditary condition play important role to understand the underlying reasonsof the diseases caused by Deoxiribole Nucleic Acid (DNA). In order to identify mutation carriersand to analyze disease,researchers tend to find various gene determinationsmethods. Nowadays, Next Generation Sequencing (NGS) is emerging as a valuable and powerful platform to detect gene-based diseasesby entiring human genome. In this study, weaimed to proposea bioinformatics application workflow to distinguish between insertions/deletions and somatic/germline mutations, by using NGS methods.Wecarried this study out on a data set containing 100 human genomesdata (20training, 80testing)for the detection of Malignant Melanoma. We foundthat the results of diagnosis performance were92.50% accuracy, 94.03% precision,96.92% sensitivity and 95.45% F1 score. These results show the potential forproposedapplicationbased on NGSto improve Melanoma detection.