rec3141 / topic-metagenomics

A repository for the lessons and notebooks used for Binder tutorials

Lesson 1: What is metagenomics?

What kinds of questions can metagenomics be used to answer?

• Taxonomy -- classification
• Function -- hmms and orthology mapping
• Molecular evolution -- binning and phylogenomics
• Community Ecology -- network analysis

Is metagenomics right for me?

• You should do amplicon sequencing instead if…
• You should do genome sequencing instead if…
• You should do transcriptomics instead if…

Lesson 2: Taxonomic Classification using kmers (with adapter-trimmed reads)

• The power of kmers
• Choosing a metagenomics classifier
  • http://ccb.jhu.edu/software/choosing-a-metagenomics-classifier/
• Demo using kraken2, centrifuge, kaiju, etc.
• • Adapter trimming using cutadapt, bbduk, etc.

Lesson 3: Taxonomic Classification using sketches (with adapter + quality filtered reads)

• How does MinHash work?
• Choosing a metagenomics sketcher
• Demo using mash, sourmash, sendsketch, etc.
• • Quality filtering using cutadapt, bbduk, etc.

Lesson 4: Taxonomic Classification using mapping (with adapter + quality filtered reads)

• How does mapping work?
• Choosing a reference genome
• Choosing a metagenomic read mapper
• Demo using bowtie, bwa, bbmap, etc.

Lesson 5: Functional Classification using HMMs (with adapter + quality filtered reads)

• How do HMMs work?
• What is an open reading frame?
• Choosing an hmm profiler
• Demo using hmmer, barrnap, etc.

Lesson 6: Functional Classification using orthologs (with merged reads)

• What is the difference between a homolog and an ortholog?
• Choosing an orthology database
• Querying an orthology database
• Demo using InterProScan, MG-RAST, MGnify, etc.
• • Read merging using FLASH, bbmerge, etc.

Lesson 7: Assembly (with error-corrected reads)

• How does sequence assembly work?
• What is a deBruijn graph?
• Choosing an assembler
• Demo using tadpole, megahit, SPAdes, etc.
• • Error correction using BayesHammer/SPAdes, tadpole, etc.

Lesson 8: Assembly Quality and Statistics (with contigs)

• How do you determine the quality of an assembly?
• Choosing an assembly quality metric
• Demo using QUAST, etc.

Lesson 9: Assembly Visualization (with assembly graph)

• What is an assembly graph useful for?
• Demo using Bandage

Lesson 10: Binning (with contigs + reads)

• How does metagenomic binning work?
• Choosing a metagenomic binner
• Demo using metabat2, CONCOCT, etc.

Lesson 11: Evaluating bins (with binned contigs)

• What are single-copy core genes?
• Choosing a bin evaluation tool
• Demo using CheckM, etc.

Lesson 12: Phylogenomics (with binned contigs)

• What are single-copy core genes?
• Basics of sequence alignment
• Basics of phylogenetic tree construction
• Demo using GToTree, GTDBtk, etc.

Lesson 13: Workflows -- Putting it all together

• A review of existing workflows
• Why you probably shouldn’t invent your own workflow
• What to do when you inevitably decide to invent your own workflow anyway
• Demo using SnakeMake, Nextflow, etc.

Lesson 14: Workflow demo: Anvi’o

Lesson 15: Workflow demo: Online Portals

• MGnify
• MG-RAST
• Galaxy
• JGI
• Cyverse
• KBase
• etc

Lesson 16: HPC

• How to use HPC to your advantage
• Common workload managers: slurm, moab, etc.

Lesson 17: Publication -- Sharing your data, results, and code

• Why you should share your data
• How to deposit your data in GenBank, EBI, etc.
• How to share your results on Figshare, etc.
• How to share your code on Github, etc.
• Best practices for writing Methods

Lesson 18: Publication -- Visualization

• Best practices for visualizing results
• Examples of bad visualizations
• Examples of good visualizations

Lesson 19: Funding

• How to write a JGI New Investigator proposal
• How to get time on XSEDE