Leveraging the Power of High Performance Computing for Genotype Calling and Next Generation Sequencing Data Analysis: Prioritizing Mutations and Enrichment Analysis

Topics to be covered by the workshop:
Sequencing alignment, sequencing variant and genotypes callings, predicting and prioritizing in silico mutations and introduction to Linux High Performance Computing (HPC) scripting.
Brief motivation:
The field of genomic has undergone major renovations and is rapidly impacting medical care across specialities. Huge advancements were made toward storing, handling, mining, comparing, extracting, clustering and analysis as well as visualization of big macromolecular data using novel computational approaches, machine and deep learning methods. Though High Performance Computing (HPC), these technological innovations have allowed scientists to tackle bigger and broader questions related to population trends, genetic variation impacts phenotype, drug response, predicting and prioritizing in silico mutations leading to clinical diagnostics and personalized medical treatment of patients on a much broader scale than ever before possible with older methods. The proposed workshop aims to introduce an interdisciplinary audience to the potential of big genomics data sciences and to key strategic considerations in mining and application to predicting and prioritizing in silico mutation and dissecting biological enrichment. Next Generation Sequencing data analysis. This hands-on training will finally equip participants to effectively prioritize mutations and perform enrichment analysis.
Target audience of the proposed workshop:
The target audience includes technicians, graduate students, postdocs and established investigators just entering the field of big genomics data sciences with the goal of bringing all up to speed on principles of sequencing alignment, sequencing variants and genotype callings, predicting and prioritizing in silico mutations and Linux High Performance Computing (HPC) scripting.