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Fundamentals of metagenomics, key applications, and its role in modern microbiome research · 60 mins — practical lessons, demonstrations and guided work included in this module.
Scope of microbiome research, databases, QC tools, metagenomic study designs, and introduction to amplicon analysis with QIIME2 · 60 mins — practical lessons, demonstrations and guided work included in this module.
QIIME2 workflow, file formats, metadata, manifest files, inputs/outputs, demultiplexing, denoising, phylogeny, and integrated tools · 60 mins — practical lessons, demonstrations and guided work included in this module.
Ecology concepts, alpha and beta diversity, statistical approaches, differential abundance analysis, and introduction to Linux for bioinformatics · 60 mins — practical lessons, demonstrations and guided work included in this module.
Setting up Windows Subsystem for Linux (WSL), command-line basics, file systems, navigation, and essential Linux commands · 60 mins — practical lessons, demonstrations and guided work included in this module.
Practical command-line exercises, Anaconda environments, installation of FastQC, MultiQC, Cutadapt/Trimmomatic, and QIIME2 command exploration · 60 mins — practical lessons, demonstrations and guided work included in this module.
Downloading metagenomic datasets using SRA Run Selector and SRA Toolkit, handling FASTQ files, and performing QC with FastQC and MultiQC · 60 mins — practical lessons, demonstrations and guided work included in this module.
Running a complete QIIME2 workflow on sequencing data, alpha/beta diversity, PCoA, phylogeny, and introduction to visualization platforms · 60 mins — practical lessons, demonstrations and guided work included in this module.
Exploring QIIME2 artifacts, visualizing results, interpreting microbiome data, summarizing the workflow, and drawing scientific conclusions · 60 mins — practical lessons, demonstrations and guided work included in this module.
Shotgun metagenomics concepts, workflow, amplicon vs. shotgun sequencing, advantages, applications, and functional annotation · 60 mins — practical lessons, demonstrations and guided work included in this module.
Complete shotgun workflow with tools including MEGAHIT, MetaBAT2, Prokka, RSEM, MetaPhlAn, and discussion of functional profiling and expected results · 60 mins — practical lessons, demonstrations and guided work included in this module.
Microbiome data visualization, commonly used plots and graphs, introduction to R, and demonstration of ggplot2 for microbiome datasets · 60 mins — practical lessons, demonstrations and guided work included in this module.
Analysis of target-gene and shotgun datasets using web-based platforms, exploring available tools and performing analysis without command-line workflows · 60 mins — practical lessons, demonstrations and guided work included in this module.
Organizing analysis outputs into a scientific report, interpreting results, presenting findings, and working through a metagenomics case study · 60 mins — practical lessons, demonstrations and guided work included in this module.
Student presentations, discussion of analysis outcomes, key learnings, feedback, and final course wrap-up · 60 mins — practical lessons, demonstrations and guided work included in this module.
Ananya is a Bioinformatics professional with a strong foundation in multi-omics and computational biology. Holding a Master’s in Systems Biology, she specializes in microbiome analysis and has worked on diverse projects spanning phylogenomics, network biology, and transcriptomics. With a strong research background and a passion for integrating theory with hands-on research, Ananya is dedicated to engaging students in genomics, microbiome research, and data-driven biological insights. She is committed to advancing bioinformatics education and fostering a deeper understanding of computational approaches across various domains of life sciences.
“Excellent course! The content is practical and the projects made the concepts much easier to apply.”
Ananya VermaPhD Scholar, India★★★★★“Hands-on projects made all the difference. The guided workflow made the analysis easier to follow.”
Rahul MehtaResearch Associate, Germany★★★★★“Very detailed and practical content. I feel much more confident now.”
Sneha PatelBioinformatics Analyst, India★★★★★Students, researchers, PhD scholars, biotechnology and life science graduates, bioinformaticians, and anyone interested in microbiome data analysis.
No. The course covers Linux, command-line tools, and metagenomics workflows from the fundamentals.
Yes. The course covers amplicon-based microbiome analysis using QIIME2 and the workflow and tools used in shotgun metagenomics.
Yes. Hands-on sessions include Linux commands, sequencing data QC, SRA data handling, QIIME2 analysis, and microbiome data exploration.
Yes. QIIME2 is covered in detail, including data formats, metadata, manifest files, demultiplexing, denoising, diversity analysis, phylogeny, visualization, and interpretation.
Yes. The course includes WSL, Linux file systems, navigation, command-line usage, and practical bioinformatics commands.
Yes. The training covers SRA Run Selector and SRA Toolkit for downloading sequencing datasets and working with FASTQ files.
Yes. The course covers the complete shotgun metagenomics workflow, major tools, functional profiling, and expected results.
MEGAHIT, MetaBAT2, Prokka, RSEM, MetaPhlAn, and other tools used across the shotgun metagenomics workflow.
Yes. The course introduces R and ggplot2 for visualization of microbiome datasets.
Yes. The course covers alpha diversity, beta diversity, PCoA, phylogenetic analysis, and interpretation of microbiome diversity results.
Yes. The course introduces statistical concepts and differential abundance approaches used in microbiome research.
Yes. MicrobiomeAnalyst is covered as a web-based platform for microbiome data analysis and visualization.
Yes. A dedicated session covers scientific report writing, results interpretation, and presentation of metagenomics findings.
Yes. The course progresses from fundamental metagenomics concepts and Linux basics to practical analysis and interpretation.
You will learn to understand metagenomics workflows, perform sequencing QC, work with QIIME2, analyze microbiome diversity, explore metagenomic datasets, visualize results, and interpret scientific findings.
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