anvi-estimate-trna-taxonomy [program]

Estimates taxonomy at genome and metagenome level using tRNA sequences..

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Authors

Can consume

profile-db contigs-db trna-taxonomy collection bin metagenomes dna-sequence

Can provide

genome-taxonomy genome-taxonomy-txt

Usage

This program uses the taxonomy associates of your tRNA sequences to estimate the taxonomy for genomes, metagenomes, or collection stored in your contigs-db.

This is the final step in the trna-taxonomy workflow. Before running this program, you’ll need to have run anvi-run-trna-taxonomy on the contigs-db that you’re inputting to this program.

Input options

1: Running on a single genome

By default, this program will assume that your contigs-db contains only a single genome and will determine the taxonomy of that single genome.

This will give you only the best taxonomy hit for your genome based on your tRNA data. If you want to look under the hood and see what results from anvi-run-trna-taxonomy it’s using to get there, add the --debug flag.

2: Running on a metagenome

In metagenome mode, this program will assume that your contigs-db contains multiple genomes and will try to give you an overview of the taxa within it. To do this, anvi’o will determine which anticodon has the most hits in your contigs (for example GGG), and then will look at the taxnomy hits for tRNA with that anticodon across your contigs.

If instead you want to look at a specific anticodon, you can specify that with the -S parameter. For example, to look at GGT, just run the following:

3: Running on multiple metagenomes

You can use this program to look at multiple metagenomes by providing a metagenomes artifact. This is useful to get an overview of what kinds of taxa might be in your metagenomes, and what kinds of taxa they share.

Running this

will give you an output file containing all taxonomic levels found and their coverages in each of your metagenomes, based on their tRNA.

4: Estimating the taxonomy of bins

You can use this program to estimate the taxonomy of all of the bins in a collection by providing the the collection and the associated profile-db.

When doing this, you can also put the final results into your profile-db as a misc-data-layers with the flag --update-profile-db-with-taxonomy

5: I don’t even have a contigs-db. Just a fasta file.

This program can run the entire ad hoc sequence search without a contigs-db involved (just a fasta and number of target sequences as a percent of the total; default: 20 percent), but this is not recommended. However, if you provide other parameters, they will be ignored.

The Output

Now that you’ve inputted your desired inputs, you think about whether you want an output and what it will look like. By default, this program won’t give you an output (just genome-taxonomy information in your contigs-db. However, if you add any of these output options, it will instead produce a genome-taxonomy-txt.

Anticodon Frequencies

If you want to look at the anticodon frequencies before getting taxonomy info at all (for example because you can’t decide which anticodon to use for input option 2), add the flag --report-anticodon-frequencies. This will report the anticodon frequencies to a tab-delimited file and quit the program.

A single output

To get a single output (a fancy table for your viewing pleasure), just add the output file path.

In this example, the input will be a single contigs-db (input option 1),

This will give you a tab-delimited matrix with all levels of taxonomic information for the genome stored in your contigs-db. Specifically, the output is a genome-taxonomy-txt.

If you want to focus on a single taxonomic level, use the parameter --taxonomic-level, like so:

You can also simplify the taxonomy names in the table with the flag --simplify-taxonomy-information

If you’re running on a profile-db, you can also choose to add the anticodon coverage to the output with --compute-anticodon-coverages.

Multiple outputs

If you have multiple outputs (i.e. you are looking at multiple metagenomes (input option number 3) or you are looking at each anticodon individually with --per-anticodon-output-file), you should instead provide a output filename prefix.

The rest of the options listed for the single output (i.e. focusing on a taxonomic level, simplifying taxonomy information, etc.) still apply.

Edit this file to update this information.

Additional Resources

Are you aware of resources that may help users better understand the utility of this program? Please feel free to edit this file on GitHub. If you are not sure how to do that, find the __resources__ tag in this file to see an example.