Day4

Day 4

Time	Activity	Slides	Hands-on
Morning	Genome-resolved metagenomics	Link here	Link here
Afternoon	Genome-resolved metagenomics		Link here

Genome-resolved metagenomics

Next step in our analysis is genome-resolved metagnomics using anvi'o. Again running all steps needed for generating the necessary files would take more time and resources for everyone to do it, so we have made a tutorial set for you. It's a subset taken from Sample03.

Tunneling the interactive interafce

Although you can install anvi'o on your own computer (and you're free to do so, but we won't have time to help in that), we will run anvi'o in the cloud and tunnel the interactive interface to your local computer.
To be able to to do this, everyone needs to use a different port for tunneling and your port will be 8080 + you user number. So user1 will use port 8081.

To connect to the cloud with your port (Linux/Mac):

ssh -i KEY.pem -L PORT:localhost:PORT USERX@IP-ADDRESS

And in windows using Putty:
In SSH tab select "tunnels". Add:

• Source port: PORT
• Destination: localhost:PORT

Click add and connect as usual.

Before doing anything else, again pull the changes from Github.

cd physalia_metagenomics
git pull origin main

Then we can start to work with our data in anvi'o.
Activate anvi'o v.7 virtual environment and copy the folder containing the tutorial files to you own course folder. Go to the folder and see what it contains.

conda activate anvio-7
cp -r ../Share/ANVI-TUTORIAL .
cd ANVI-TUTORIAL
ls -l

You should have there the CONTIGS.db and PROFILE.db plus an auxiliary data file called AUXILIARY-DATA.db.

First have a look at some basic statistics about the contigs database.
NOTE! You need to specify your port.

anvi-display-contigs-stats CONTIGS.db -P PORT

Now anvi'o tells you to the servr address. It shoudl contain your port number. Copy-paste the address to your favourite browser. Chrome is preferred.

One thing before starting the binning, let's check what genomes we might expect to find from our data based on the single-copy core genes (SCGs).

anvi-estimate-scg-taxonomy -c CONTIGS.db \
                           -p PROFILE.db \
                           --metagenome-mode \
                           --compute-scg-coverages

Then you can open the interactive interface and explore our data and the interface.
NOTE! You need to specify your port in here as well.

anvi-interactive -c CONTIGS.db -p PROFILE.db -P PORT

You might notice that it's a bit slow to use sometimes. Even this tutorial data is quite big and anvi'o gets slow to use when viewing the whole data. So next step is to split the data in to ~ 5-8 clusters (bins) that we will work on individually.

Make the clusters and store them in a collection called PreCluster. Make sure that the bins are named Bin_1, Bin_2,..., Bin_N. (or anything else easy to remember).
Then you can close the server from the command line.

Next we'll move on to manually refine each cluster we made in the previous step. We'll do this to each bin in our collection called PreCluster.

To check your collections and bins you can run anvi-show-collections-and-bins -p PROFILE.db

If you know what you have, go ahead and refine all the bins on your collection. After refining, remember to store the new bins and then close the server from command line and move on to the next one.

anvi-refine -c CONTIGS.db -p PROFILE.db -C COLLECITON_NAME -b BIN_NAME -P PORT

After that's done, we'll rename the bins to a new collection called PreliminaryBins and add a prefix to each bin.

anvi-rename-bins -c CONTIGS.db -p PROFILE.db --collection-to-read Precluster --collection-to-write PreliminaryBins --prefix Preliminary --report-file REPORT_PreliminaryBins

Then we can also make a summary of the bins we have in our new collection PreliminaryBins.

anvi-summarize -c CONTIGS.db -p PROFILE.db -C PreliminaryBins -o SUMMARY_PreliminaryBins

After that's done, copy the summary folder to your local machine ands open index.html.

From there you can find the summary of each of your bins. In the next step we'll further refine each bin that meets our criteria for a good bin but still has too much redundancy. In this case completeness > 50 % and redundancy > 5 %. So refine all bins that are more than 50 % complete and have more than 5 % redundancy.

When you're ready it's time to again rename the bins and run the summary on them.
Name the new collection Bins and use prefix Sample03.

Now we should have a collection of pretty good bins out of our data. The last step is to curate each bin to make sure it represent only one population. And finally after that we can call MAGs from our collection. We will call MAGs all bins that are more than 80 % complete and have less than 5 % redundancy.

anvi-rename-bins -c CONTIGS.db -p PROFILE.db --collection-to-read Bins --collection-to-write MAGs --prefix Sample03 --report-file REPORT_MAGs \
                  --call-MAGs --min-completion-for-MAG 80 --max-redundancy-for-MAG 5

And finally you can make a summary of your MAGs before moving on.

anvi-summarize -c CONTIGS.db -p PROFILE.db -C MAGs -o SUMMARY_MAGs