Metagenome-assembly-and-binning

Current workflows in the symbiosis department

Step 1 -- I have a bunch of reads, now what?

Metagenome sequencing reads

• Check your reads with FastQC
• Check what organisms are there: PhyloFlash for 16S rRNA and COI
• Quality trim your reads. We often use a quality of 2 since the reads get a higher quality after error correction (Bbduk). Remove PhiX, TruSeq adaptors.
• If your paired-end reads overlap, try merging the reads (Bbmerge).
• HGV tip: Check the K-mer spectrum.
• Assemble your reads (e.g. Megahit, MetaSPades, IDBA_UD)
  • Megahit: Fast, but produces highly fragmented assemblies
  • MetaSpades: Crashes often with more than one library. Slow
  • IDBA_UD: Produces good N50, and has a good running time. The output does not include an assembly graph.

Step 2 -- Assembly

Before proceeding think about the following:

• Does it make sense to pool the reads of different libraries together?

If yes, do you have access to a computer that can deal with all the data?

• If you only have the sequencing of one sample, then assemble the one library. If your assembly is completely crappy, consider sequencing more samples.
• Kmer 127: for reads >150 bp and coverage >5X
• Brandon's script combines scaffold with graph

Step 3 -- Binning

• Differential coverage and GC% (e.g. GBTools)
• Taxonomy (Blobology, Phyla-Amphora)
• Check RNA (e.g. Barrnap)
• Linkage analysis (e.g. Bandage or Albertsen protocol)

Check quality control of the assembled genomes (See step 5)

Step 4 -- Reassembly

• Often improves assembly metrics, but you should try it yourself.
• More work and not scalable to many data sets.

Step 5 -- Quality control of assembly

• CheckM (Prokaryotes)
• BUSCO (Eukaryotes)
• Quast

Optional:

• Phylogenomic placement
• ANI (e.g. Jspecies, or Kostas website)

Other resources

• Stephen Turner's blog about genetic tips and other informatic news: http://www.gettinggeneticsdone.com/
• Adrien's blog on his rambling about bioinformatic, include tutorials and scripts examples: http://aassie.net/Pro/
• Nature computational biology journal collection of fundamental paper exaplaining computational concept (eg. Bayesian statistic, Debruijn graph, etc...): http://www.nature.com/nbt/collections/compbio/index.html

About this repository

This repository contains results from metagenome binning roundtable discussion moderated by Liz S on 26 Sep 2016. Sharing it as a Git repository has three aims - (i) make it possible to edit it collaboratively, (ii) for newbies, have some practice using Git and Github for a simple project, and (iii) take advantage of the Markdown formatting to start building a simple webpage that can be used as a reference on metagenome binning.

Formatted in Markdown - learn more about the syntax here.

Learn more about Git and Github from the Github help pages, and Symbiosis wiki (internal link)

Suggested workflow:

• Get a Github account if you don't have one already.
• Fork this repository and clone it to your local machine.
• Edit the text, create new pages, insert links, images, etc.
• Commit those changes. (Tip: Commit small "chunks" of changes at a time, so that they can be easily undone if necessary, and document your commits with short but descriptive commit messages.)
• Push changes back to Github.
• Submit a pull request for Liz to merge your changes with the master version of the repository.