Antofagasta 2025 workshop - LangilleLab/microbiome_helper GitHub Wiki

This page will provide an overview of the bioinformatics workshop taking place in Antofagasta, Chile, between June 17-20 and 23-25, 2025.

Instructor: Robyn Wright

Workshop format

The workshop will be split into two sections: Marker Gene Analysis and Shotgun Metagenome Analysis. Each section will start with an initial short lecture to ensure that participants understand the general concepts. Participants will then work through a typical analysis workflow with tutorial data. The participants will then be provided with a dataset to use as a Case Study; this will test how well they have understood the concepts introduced with the tutorial data. Bioinformatic analyses of real-world data rarely fit neatly with the exact steps carried out by previous studies, so this will ensure that participants learn the problem-solving skills necessary for analysing their own data. Finally, there will be time for participants to either work on their own data analysis with support from the instructor, or to ask the instructor questions about anything related to microbiome sequencing data analysis.

Each section of this workshop will build upon the prior sections, requiring participants to apply what they have learnt, consolidating their new skills. It is also structured to help them to build confidence in their data analysis abilities prior to performing the analyses on their own data. In reality, the computational time required alone means that it takes far longer than a week to perform bioinformatic analyses of microbiomes, but through the succession of tutorial data to case study to their own data, participants should develop the required skills for independent analysis of their own sequencing data.

It is assumed that participants either attended the ICG workshop last year or have some prior experience of their own in R, Python, Unix or similar (i.e., they understand the basic principles of reading and writing programming languages).

Marker Gene Analysis

Course Objectives

Participants will gain practical experience and skills to be able to:

  • Understand the advantages and limitations of marker gene data analysis
  • Devise an appropriate bioinformatics workflow for processing and analysing microbiome marker-gene sequence data
  • Apply appropriate statistics to undertake rigorous data analysis

Topics covered

  • Introduction to cloud computing
  • Quality control of sequencing data in a Unix command line
  • 16S analysis (Illumina and PacBio) workflow using QIIME2 in a Unix command line: importing of reads, denoising and ASV generation, taxonomic classification of reads, insertion of reads into a phylogenetic tree
  • Overview of microbial ecology metrics (alpha and beta diversity)
  • Challenges with microbiome data and compositionality
  • Testing for statistical differences in alpha and beta diversity and detecting differentially abundant taxa between sample groups
  • Visualisation of all results obtained

Shotgun Metagenome Analysis

Course Objectives

Participants will gain practical experience and skills to be able to:

  • Understand the advantages and limitations of metagenomic data analysis
  • Devise an appropriate bioinformatics workflow for processing and analysing microbiome shotgun metagenomic sequence data
  • Perform both read-based (short-read) and assembly-based (short and long-read) analyses of shotgun metagenomic sequence data

Topics covered

  • Comparison of major approaches (read based vs assembly based and long read vs short read)
  • Importance of sequencing depth and host contamination
    • Techniques for removal of host contamination using Kneaddata in the Unix command line
  • Approaches for assigning taxonomy to shotgun metagenomic data
    • Taxonomic profiling of short reads using Kraken or MetaPhlAn in the Unix command line
    • Visualisation of results obtained by applying what was learnt in the Marker Gene Analysis workshop
  • Overview of metagenomic assembly and binning and quality metrics used
    • Assembly of short reads into contigs, binning of contigs and refinement of bins into Metagenome Assembled Genomes (MAGs) using Anv’io in the Unix command line
  • Methods for assigning functions to reads or contigs, and the differences in approaches for assigning functions to all reads versus specific groups of functions such as Antimicrobial Resistance (AMR) or carbohydrate metabolism genes
  • General functional annotation using MMSeqs and AMR annotation of reads using CARD RGI in the Unix command line
  • Visualisation of results obtained by applying what was learnt for the taxonomic annotation of reads
  • Stratifying functions by taxonomy
    • Visualisation of stratified functions by taxonomy

Workshop schedule

June 17-20 and 23-25, 2025

Day Date Session
Day 1 Tuesday June 17th Marker Gene Analysis Tutorial
Day 2 Wednesday June 18th Marker Gene Analysis Case Study / own data / Q&A
Day 3 Thursday June 19th Marker Gene Analysis Case Study / own data / Q&A
Day 4 Friday June 20th Shotgun Metagenome Analysis Tutorial
Day 5 Monday June 23rd Shotgun Metagenome Analysis Case Study / own data / Q&A
Day 6 Tuesday June 24th Shotgun Metagenome Analysis Case Study / own data / Q&A
Day 7 Wednesday June 25th Shotgun Metagenome Analysis Case Study / own data / Q&A

Daily schedule

Time Activity
9:00-9:30 Arrival
11:00-11:30 Coffee break
13:00-14:30 Lunch
17:00 Finish for the day

Note that during the workshop sessions will be a mixture of the instructor walking the participants through the steps involved in microbiome analyses and the participants working through the workshop materials in a self-paced manner, with the instructor available to help them if/when they get stuck. We may switch parts of the workshop depending on the pace needed by the group, but do not intend to over-run any of the sessions.

Workshop pages

Marker Gene Analysis

Previous lectures for review:

Shotgun Metagenome Analysis

Previous lectures for review:

Labs

  1. Command line fundamentals
  2. Marker gene workflow with PacBio data in QIIME2 (Optional) Predicting functions from marker gene data
  3. Alpha/beta diversity and differential abundance using Phyloseq in R
  4. Read-based metagenomic analyses:
    1. Run Kneaddata
    2. Taxonomic annotation of reads
    3. Getting a phylogenetic tree
  5. Assembly of MAGs in Anvi'o
    1. Run Kneaddata
    2. MAG assembly, binning and curation with Anvi'o
  6. Advanced plotting options:
    1. Apply what you learnt from the marker gene analyses to the metagenomic data
    2. Apply the advanced plotting and analysis to this metagenomic dataset