The microbiome of a patient is suspected to have a significant influence on his risk of developing cancer as well as his chances of survival. Therefore, sequencing the genome of bacteria can help to investigate this presumption. But the 16s-rRNA pipeline involved in the microbiome analysis includes a time-consuming step of matching data files. This step is optimized in this research paper in order to save time and avoid additional biases. To achieve this objective, a program is developed in python. This program is designed to be user-friendly and easy to adapt in the future as the pipeline evolves. It was used on recent clinical data where the significance of antibiotic medication and chemotherapy on the microbiome was examined. This investigation led to the result that there is no significant correlation between the microbiome of a patient and the fact whether he received antibiotic medication or chemotherapy in recent times. Nevertheless, this program can be used in any 16s-rRNA analysis in medical and non-medical fields to ensure better results in less time.