Microbiome Data Analysis: Processing and Interpreting Sequencing Data

The study of microbial communities is transforming medicine, agriculture, and environmental science, but making sense of raw sequencing data can be overwhelming. This course provides a clear, step-by-step path to understanding how microbiome data is generated, processed, and analyzed. Through comprehensive written explanations and practical code examples, you will transition from a beginner to a confident practitioner capable of handling microbiome datasets. You will learn how to clean raw sequence reads, assign taxonomy, calculate diversity metrics, and identify significant differences between microbial communities. What you'll learn: - Understand foundational microbiome concepts, sequencing technologies, and marker-gene versus metagenomic approaches. - Process raw sequencing reads using modern denoising pipelines to identify exact sequence variants. - Classify taxonomic groups and interpret microbial community compositions. - Calculate and compare alpha and beta diversity metrics to measure community variation. - Perform differential abundance testing using modern statistical packages to find key biomarkers. - Apply reproducible research practices to document and share your bioinformatics workflows. The course begins with essential biological and sequencing terminology before guiding you through sequence quality control, taxonomic classification, and statistical analysis. You will practice interpreting real-world datasets using clear, written walkthroughs and code snippets. This course is designed for beginners, including life scientists, students, and data enthusiasts looking to enter the field of bioinformatics. No prior experience with microbiome analysis is required, though a basic familiarity with command-line tools or programming is helpful. Start reading today to unlock the secrets of microbial communities and elevate your data analysis skills.