Next generation sequencing (NGS) to identify the potential of diseases in an individual

This publication details my genomic sequencing research project's process, findings, and methods at the University of Chicago's 2022 summer program. The course "Mathematical and Computational Methods in Biological Sciences Research”, offers students the opportunity to sequence and compare a human genome to a reference genome to identify sources of genomic mutations and analyze the trends in certain genes and their relation to causative disorders or diseases. For this project, I Used R programming techniques, with the aid of Uchicago's supercomputers. My team and I identified DNA variations to discover diseases that the sample individual might be predisposed to, or have a higher chance of developing certain forms of cancer. The Burrows-Wheeler alignment (BWA) was used to align the DNA strand with the reference strand due to its consistency and speed. The Sampe algorithm was leveraged to load the entire FM index(a compressed full-text substring index based on the Burrow-Wheeler transform) into memory to reduce disk operations. I Used the tool Annovar to annotate each mutation with information. Annovar uses RefSeq. ENSEMBL genes, GENECODE genes, and ACeView genes to identify each gene. Leveraged the NCBI (National Center for Biotechnology Information) database to narrow down the disease.