DETERMINATION OF MALIGNANT MELANOMA BY ANALYSIS OF VARIATION VALUES

Melanoma is a serious disease associated with mutation-based cancer cells. Genetic structure and hereditary condition play important role to understand the underlying reasons of the diseases caused by Deoxiribole Nucleic Acid (DNA).  In order to identify mutation carriers and to analyze disease, researchers tend to find various gene determinations methods. Nowadays, Next Generation Sequencing (NGS) is emerging as a valuable and powerful platform to detect gene-based diseases by entiring human genome. In this study, we aimed to propose a bioinformatics application workflow to distinguish between insertions/deletions and somatic/germline mutations, by using NGS methods. We carried this study out on a data set containing 100 human genomes data (20 training, 80 testing) for the detection of Malignant Melanoma. We found that the results of diagnosis performance were 92.50% accuracy, 94.03% precision, 96.92% sensitivity and 95.45% F1 score. These results show the potential for proposed application based on NGS to improve Melanoma detection