Keywords: microbiome

Learning objectives:

• Annotate features on the identified plasmids using mobile genetic element database annotations.
• Apply Kraken and MetaPhlAn to assign taxonomic labels
• Apply Krakentools to calculate α and β diversity and understand the output
• Apply Krona and Pavian to visualize results of assignment and understand the output
• Apply appropriate tools for analyzing the quality of metagenomic assembly
• Apply appropriate tools for analyzing the quality of metagenomic data
• Assess long reads FASTQ quality using Nanoplot and PycoQC
• Assess short reads FASTQ quality using FASTQE 🧬😎 and FastQC
• Binning of contigs into metagenome-assembled genomes (MAGs) using MetaBAT 2 software
• Check quality reports generated by FastQC and NanoPlot for metagenomics Nanopore data
• Choose the best approach to analyze metatranscriptomics data
• Construct a final annotated dataset integrating genetic element information for downstream applications.
• Construct and apply simple assembly pipelines on short read data
• Describe common problems in metagenomics binning
• Describe what an assembly is
• Describe what de-replication is
• Describe what metagenomics binning is
• Evaluate plasmid coverage to determine effective filtering thresholds.
• Evaluate the Quality of the Assembly with Quast, Bowtie2, and CoverM-Genome
• Evaluate the distribution of mapping scores to identify high-quality alignments.
• Evaluation of MAG quality and completeness using CheckM software
• Explain different metrics to calculate α and β diversity
• Explain how taxonomic assignment works
• Explain how tools based on De Bruijn graph work
• Explain the difference between co-assembly and individual assembly
• Explain the difference between reads, contigs and scaffolds
• Explain what taxonomic assignment is
• Explain what taxonomic diversity is
• Familiarize yourself with the basics of Galaxy
• Filter alignments based on plasmid coverage and mapping quality.
• Generate a curated table of plasmid sequences and convert it into a FASTA file for further analysis.
• Identify pathogens based on the found virulence factor gene products via assembly, identify strains and indicate all antimicrobial resistance genes in samples
• Identify pathogens via SNP calling and build the consensus gemone of the samples
• Identify taxonomic classification tool that fits best depending on their data
• Identify yeast species contained in a sequenced beer sample using DNA
• Inspect metagenomics data
• Justify the filtering thresholds chosen for identifying plasmid sequences.
• Learn how histories work
• Learn how to create a workflow
• Learn how to extract and run a workflow
• Learn how to obtain data from external sources
• Learn how to run tools
• Learn how to share a history
• Learn how to share your work
• Learn how to upload a file
• Learn how to use a tool
• Learn how to view histories
• Learn how to view results
• Perform metagenomics read mapping against mobile genetic element database.
• Perform quality correction with Cutadapt (short reads)
• Perform taxonomy profiling indicating and visualizing up to species level in the samples
• Preprocess the sequencing data to remove adapters, poor quality base content and host/contaminating reads
• Process single-end and paired-end data
• Relate all samples' pathogenic genes for tracking pathogens via phylogenetic trees and heatmaps
• Run metagenomics tools
• Summarise quality metrics MultiQC
• Understand the functional microbiome characterization using metatranscriptomic results
• Understand where metatranscriptomics fits in 'multi-omic' analysis of microbiomes
• Use tools to process sequences, ensuring data is sorted, deduplicated, and formatted correctly.
• Visualise a community structure
• Visualize the microbiome community of a beer sample
• What software tools are available for metagenomics binning

Event types:

• Workshops and courses

Sponsors: Australian BioCommons, ELIXIR Europe, Erasmus Medical Center, The Pennsylvania State University, University of Freiburg, de.NBI

Scientific topics: Metagenomics, Microbial ecology, Taxonomy, Sequence analysis, Sequence assembly, Metatranscriptomics, Function analysis, Genomics, Microbiology, Mobile genetic elements, Public health and epidemiology, Pathology