mykrobe-lineage-test

This repository contains code for testing mykrobe species and lineage calls, and results of the testing. It is intended for mykrobe developers, for testing mykrobe species/lineage calls and tracking the results.

There are two directories:

1. Python/: this contains the code, and a Singularity definition file that makes a container with the code plus the dependencies.
2. Analysis/: contains results of testing mykrobe species and lineage calls.

For results, please see the readme in the Analysis/ directory.

Installation

This repository has a main script called mlt (acronym for "mykrobe lineage test", yes we are testing species calls as well but "mykrobe lineage species test" seemed like a bad name!).

Singularity

The easiest way is to build a singularity container.

cd Python
sudo singularity build mlt Singularity.def

Run like that, singularity will make a container file called mlt. You can just treat it as an normal executable, no need to run singularity exec mlt unless you want to.

Source

If you want to run locally, then you will need these in your $PATH:

• enaDataGet, which is from enaBrowserTools (have a look in Singularity.def)
• mykrobe.
• (also fastaq and ncbi-genome-download are required, but are installed when you install mlt because they are in the requirements file.)

Then run pip install . from the Python/ directory. The required python packages will be installed (they are in requirements.txt).

Alternatively, you could not do pip install, and instead do this:

PYTHONPATH=/path_to/mykrobe-lineage-test/Python /path_to/mykrobe-lineage-test/Python/mlt/__main__.py

That command is equivalent to running the script mlt.

Testing lineage calls

In short, the process is:

1. Put your sample info in a TSV file.
2. Download reads using mlt download_data
3. Run mykrobe on all samples using mlt run_mykrobe
4. Make a summary of the results using mlt summary.

sample TSV

All the commands need a TSV of sample information. The format is like this (this is made up data!):

accession   source  species                     lineage
SRR12345678 ena     Mycobacterium_tuberculosis  lineage1.2.3
GCF_1234567 genbank Mycobacterium_tuberculosis  lineage2.3.4
XY123456    refseq  Mycobacterium_tuberculosis  lineage3.4

You must have columns accession, source, species and lineage. They can be in any order (and any extra columns are ignored). The lineage can be "NA" if there is no lineage call and you just want to test the species call.

The source must be ena, genbank, or refseq, and the accession column should have the corresponding ENA run ID, or genbank/refseq genome accession. Since reads are needed for mykrobe, reads are simulated from genomes using fastaq to_perfect_reads, making perfect reads (ie no snp/indel errors) of length 75bp, fragment size 200, and depth 20X.

Download data

With a TSV file of samples samples.tsv in the above format, run:

mlt download_data --cpus 3 samples.tsv Reads

That example downloads 3 samples in parallel. It makes a directory called Reads containing the downloaded data. It will (well, should) not crash on failed downloads, but carry on and get all the samples it can. Check stderr to see what happened.

You can rerun on an existing directory and it will only try to get data that is missing and skip the samples that are already downloaded. This also means you can do hacks like different sample TSV files run against the same directory of a superset of reads, if you're feeling fancy.

Run mykrobe

Assuming you have a directory of downloaded reads from mlt download_data called Reads/:

mlt run_mykrobe --cpus 10 samples.tsv Reads Results

That will run 10 samples in parallel. It makes a new directory (if it doesn't exit already) called Results. As for download_data, you can rerun against the same directory and it will only run samples that do not already have a mykrobe json file of results. It will ignore samples in the TSV with no reads in Reads/. It's up to you to use the right TSV file/Reads directory/results directory - there is no sanity checking. This does allow for more hacking and testing of samples.

IMPORTANT: the first time a sample is run in Results/, there is no skeletons file. If you ask for more than one CPU, the first sample will be run on its own, making the skeletons file. Then the remaining samples are run using multiprocessing, since they can then all use the skeletons file, instead of all trying to make one at the same time and crashing.

There is an option --panels_dir, which will use that option with mykrobe, so that you can override the default panels directory and use your own. You probably want this, since the point here is to test species/lineage calls. It is not recommended to change the panel and then use an existing results directory because the skeletons file that is already might be used!

Summarise results

Assuming you have a samples TSV file samples.tsv, a directory of reads called Reads/, and a directory of mykrobe runs called Results/:

mlt summary samples.tsv Reads Results summary.tsv

That makes a new TSV file called summary.tsv. It is the same as samples.tsv, but with added columns:

• called_species and called_lineage. These are the calls made by mykrobe.
• correct: this is true|false, showing if the both the called species and lineage were correct. If the expected lineage is "NA", then the true/false call only depends on the species.

Now be good and record the results in the Analysis/ directory and push to github.