Usage
First, make sure you have sshpass
installed.
Next, set the following environment variables, which are used to log into the LBL server.
LBL_USER
LBL_PASSWORD
Optionally, set up a Python virtual environment and install the requirements (or just install the requirements):
python3 -m venv _venv
source _venv/bin/activate
python3 -m pip install -r requirements.txt
Before running, you will need to mirror some of the files from the LBL server to your local machine. This includes selecting the "best" reference genome from the available genomes in the master sample's reference_genome
directory. This is done based on the ANI score compared to the Unicycler assembly. While there are other assembly FASTAs to use, the Unicycler assembly is always used in this process.
make prepare
Now you're ready to go! Running the following will create build/alignments.csv
:
make align
This output contains the following:
sample
: master sample IDref_genome
: reference genome used (selected fromdata/iarpa/TE/[sample]/reference_genome
)seq_id
: element sequence IDref_start
: start of alignment in reference genomeref_end
: end of alignment in reference genomeassembly_start
: start of alignment in Unicycler assemblyassembly_end
: end of alignment in Unicycler assembly