This Genomic Data Analysis course provides a complete introduction to the basics of genomics and genetic data analysis for beginners. It focuses on understanding how biological data is structured and analyzed using computational tools.

The course begins with an introduction to genomic data analysis and explains key concepts such as SNPs (single nucleotide polymorphisms), which are fundamental units of genetic variation. It then explores SNP genotype data files and how they are used in real-world research.

You will learn how to work with PLINK, a widely used tool in genetics for handling and analyzing large-scale genomic datasets. The course covers data formatting, quality control, and preparing datasets for analysis.

In addition, it introduces R and RStudio for statistical computing, helping learners perform data analysis and visualization.

The course also explains principal component analysis (PCA), which is used to understand patterns and relationships in genetic data.

By the end of this course, learners will have a basic understanding of genomic data structures, SNP analysis, PLINK usage, and statistical methods used in genetics research.