Genomic Data Analysis is a 3-month program that will provide an in-depth overview of standard tools and data types used to study genomics datasets. Each week, participants will meet online to discuss various aspects of genomics analysis and interpretation and work on independent projects throughout this course. Read more about the program and important dates: http://bit.ly/31WX0tj
Session will cover: 1. Overview of the tools and resources for this program (edu.t-bio.info courses, projects and datasets and the T-BioInfo Analytics Platform) 2. Expectations and...
What is DNA, Variation, and Significance Next Generation Sequencing (WES, WGS, Targeted panels) Read length/quality, Mapping NGS data to a reference Genome
Germline variation Somatic mutations – reference and “normal” sample Non-point variations (CNV, chromosomal instability, rearrangements)
Accurate detection – the significance of coverage distribution Filtering – limiting the number of potentially significant variants Statistical methods for significance, stratification
Regression, factors, and features – Factor Regression Analysis Supervised Machine Learning (Classification, Discriminant Analysis) Mutational Profiling, Signatures, and biomarkers
Cancer studies (several examples) Development of treatment resistance (Tuberculosis) Case-control studies, GWAS (Breast Cancer Risk)