Cancer Genomic Workshop
Decode the mutational landscape of oncology using high-throughput sequencing data and advanced bioinformatic tools. Master clinical genomic alignment pipelines and somatic variant interpretation through five days of intensive hands-on sessions.
Course Description
This intensive 5-day online workshop delivers a robust computational deep-dive into the field of cancer genomics for modern life science research. Participants will explore multi-omic data structures, mastering the software workflows required to identify driver mutations and structural variations across complex tumor samples. The curriculum covers the entire digital pipeline from processing raw sequencing files to executing comparative somatic vs. germline analysis frameworks. By leveraging smart sequence alignment algorithms and automated variant calling protocols, you will learn to separate background noise from pathogenic genetic alterations. This practical training bridges the gap between big data oncological repositories and translational clinical insight without requiring previous command-line proficiency. Through guided computational exercises, you will discover how to cross-reference identified mutational signatures with globally recognized precision medicine databases. Elevate your quantitative research capabilities, minimize common data bottlenecks, and unlock predictive biological workflows tailored for modern oncological diagnostics.
What You'll Learn
The fundamental molecular mechanisms, chromosomal alterations, and genomic hallmarks driving cancer progression.
How to run, evaluate, and optimize quality control workflows on raw high-throughput tumor sequencing data.
Proven computational methods to perform reference genome sequence alignments and identify somatic variants.
Strategies to utilize algorithmic tools to distinguish oncogenic driver mutations from passenger alterations.
Practical approaches for navigating public clinical databases to annotate, score, and interpret target variants.
Curriculum
-
Module 1: Molecular biology of oncogenesis, clonal tumor evolution, and the architecture of next-generation sequencing (NGS) in oncology.
Lesson -
Module 2: Pre-processing raw cancer sequencing data, reference genome mapping, and tumor-normal pair alignment pipelines.
Lesson -
Module 3: Running advanced somatic variant callers (MuTect2) and calculating subclonal copy number alterations.
Lesson -
Module 4: Utilizing AI-driven predictive modeling to map driver mutations to targeted therapeutics and drug-resistance pathways.
Lesson -
Module 5: Curation of variants using ACMG/AMP guidelines, generating clinical genomics reports, and rendering final multi-omics data plots.
Lesson
