Advance 15 Days Metagenomics Data Analysis Training.

This course is designed for students, researchers, and professionals who are interested in understanding and applying bioinformatics techniques to analyze metagenomic data. Upon completing this training, you will become an expert in metagenomics and be able to independently undertake projects involving metagenomics and next-generation sequencing (NGS). Book your seat now and begin your journey into the world of metagenomics!

Registration
Ananya Ghosh

Educator

Ananya Ghosh

Difficulty

Basics to Advance

Mode

Live Session

language

Language

English

About Course

This Metagenomics Data Analysis course provides an in-depth understanding of the tools, techniques, and methodologies required to analyze complex metagenomic data. It is tailored for students, researchers, and professionals who wish to develop expertise in bioinformatics and the application of next-generation sequencing (NGS) technologies in microbial community analysis.

Throughout the course, participants will learn how to process and analyze large-scale sequencing data, explore microbial diversity, and interpret functional genomic information from environmental samples. The curriculum covers a wide range of topics, including raw data quality control, metagenomic assembly, taxonomic classification, functional annotation, and statistical analysis of microbial communities. Additionally, hands-on experience with popular bioinformatics tools such as FASTQC, DADA2, and QIIME2 will equip participants with the practical skills needed to carry out independent metagenomics projects.

By the end of the course, students will be proficient in metagenomics data analysis and capable of executing real-world projects in areas such as microbiome research, environmental monitoring, and clinical applications. Whether you are looking to enhance your research, transition into bioinformatics, or dive deeper into microbial community analysis, this course will set you on the path to becoming a confident and skilled practitioner in the field of metagenomics.

Metagenomics Data Analysis Training

Day-1

Introduction to Metagenomics

  • Agenda: Understand the basics of metagenomics and NGS data formats (FASTA, FASTQ), and their relevance in microbiome research.
  • Outcome: Gain a strong theoretical foundation to start practical applications.
  • Tools: None (theoretical session) 

Day-2

Environmental Setup

  • Agenda: Install essential tools like QIIME2 and FastQC. Learn basic Linux commands to navigate and manage bioinformatics workflows.
  • Outcome: Set up a functional environment for metagenomics analysis.
  • Tools: Linux commands, QIIME2, FastQC

Day-3

Quality Control of Raw Data

  • Agenda: Perform quality control on raw sequencing data and interpret FastQC reports to identify potential issues.
  • Outcome: Understand how to assess and ensure the quality of sequencing data.
  • Tools: FASTQc
  • Take home assignment

Day-4

Read Trimming and Filtering

  • Agenda: Remove adapters and low-quality reads to prepare clean datasets for analysis.
  • Outcome: Learn preprocessing techniques essential for accurate downstream analysis.
  • Tools: cutadapt, QIIME2.
  • Take home assignment

Day-5

Taxonomic Profiling

  • Agenda: Classify microbial communities using MetaPhlAn and visualize taxonomic distributions.
  • Outcome: Identify microbial taxa present in your dataset and interpret their roles.
  • Tools: MetaphlAn
  • Take home assignment

Day-6

Alpha Diversity Analysis

  • Agenda: Measure species diversity using metrics like Shannon and Simpson
    indices.
  •  Outcome: Evaluate within-sample diversity and its ecological significance.
  • Tools: QIIME2 (diversity metrics)
  • Take home assignment

Day-7

Beta Diversity Analysis

  • Agenda: Compare microbial community structures across samples and
    visualize differences using PCoA plots.
  • Outcome: Understand sample clustering and relationships between
    microbial communities.
  • Tools: QIIME2, Matplotlib.
  • Take home assignment

Day-8

Differential Abundance Analysis

  • Agenda: Identify significant differences in microbial taxa between groups
    using statistical tools.
  • Outcome: Analyze how different conditions impact microbial communities.
  • Tools: DESeq2 (R).
  • Take home assignment

Day-9

Functional Profiling

  • Agenda: Predict metabolic pathways and functional annotations from
    metagenomics data.
  • Outcome: Understand the functional capabilities of microbial communities.
  •  Tools: HUMAnN.
  • Take home assignment

Day-10

Assembly of Shotgun Data

  • Agenda: Assemble shotgun sequencing reads and annotate functional
    profiles.
  • Outcome: Gain skills in reconstructing microbial genomes and identifying
    gene functions.
  • Tools: SPAdes, Prokka.
  • Take home assignment

Day-11

Advanced Data Visualization

  • Agenda: Create heatmaps, bar plots, and combined visualizations to
    interpret complex data.
  • Outcome: Learn to present data effectively for reports and presentations.
  • Tools: ggplot2 (R), Python Matplotlib.
  • Take home assignment

Day-12

Dataset Exploration

  • Agenda: Access and evaluate microbiome datasets from public repositories
    like MGnify and NCBI.
  • Outcome: Learn how to integrate public datasets into your research.
  • Tools: MGnify, NCBI.
  • Take home assignment

Day-13

Report Writing and Results Interpretation

  • Agenda: Compile your analysis results into a structured scientific report.
  • Outcome: Gain experience in summarizing findings and preparing a
    comprehensive report.
  • Take home assignment

Day-14

Processing of Shotgun Data

  • Agenda: Create an engaging presentation summarizing your findings from
    the course.
  • Outcome: Learn how to effectively communicate scientific results to an
    audience.
  • Tools: PowerPoint or Google Slides.
  • Take home assignment

Day-15

Assembling Data for Taxonomy and Function

  • Agenda: Present your analysis and key insights to peers, followed by a
    discussion on challenges and takeaways.
  • Outcome: Build confidence in presenting research findings and receive
    constructive feedback.
  • Tools: PowerPoint or Google Slides.
  • Take home assignment
Ananya Ghosh

Educator - Ananya Ghosh

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.

Metagenomics Complete Data Analysis from Basics to Advance

Mode - Live Session

Certificate Provided

Hours 15 - 20 Hours

Session Time: 7:00 PM IST

Last Date 01 April

Course Start Date 7 April

Recorded lecture will be Provided

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