plantref.databio.org server overview

This repository contains the files to build and archive genome assets to serve with refgenieserver at http://plantref.databio.org.

The whole process is scripted, starting from this repository. From here, we do this basic workflow:

1. Download raw input files for assets (FASTA files, GTF files etc.)
2. Build assets with refgenie build in a local refgenie instance
3. Archive assets with refgenieserver archive
4. Deploy assets to active server on AWS.

Adding an asset to this server

Overview of metadata structure

The metadata is located in the asset_pep folder, which contains a PEP with metadata for each asset. The contents are:

• assets.csv - The primary sample_table. Each each row is an asset.
• recipe_inputs.csv - The subsample_table. This provides a way to define each individual value passed to any of the 3 arguments of the refgenie build command: --assets, --params, and --files.
• refgenie_build_cfg.yaml -- config file that defines a subproject (which is used to download the input data) and additional project settings.

Step 1: Add the asset to the asset table.

To add an asset, you will need to add a row in assets.csv. Follow these directions:

• genome - the human-readable genome (namespace) you want to serve this asset under
• asset - the human-readble asset name you want to serve this asset under. It is identical to the asset recipe. Use refgenie list to see available recipes

Your asset will be retrievable from the server with refgenie pull {genome}/{asset_name}.

Step 2: Add any required inputs to the recipe_inputs table

Next, we need to add the source for each item required by your recipe. You can see what the recipe requires by using -q or --requirements, like this: refgenie build {genome}/{recipe} -q. If your recipe doesn't require any inputs, then you're done. If it requires any inputs (which can be one or more of the following: assets, files, parameters), then you need to specify these in the recipe_inputs.csv table.

For each required input, you add a row to recipe_inputs.csv. Follow these directions:

• sample_name - must match the genome and asset value in the assets.csv file. Format it this way: <genome>-<asset>. This is how we match inputs to assets.

Next you will need to fill in 3 columns:

• input_type which is one of the following: files, params or assets
• intput_id must match the recipe requirement. Again, use refgenie build <genome>/<asset> -q to learn the ids
• input_value value for the input, e.g. URL in case of files

Step 3: See if you did it well!

Validate the PEP with eido

The command below validates the PEP against a remote schema. Any PEP issues will result in a ValidationError:

eido validate refgenie_build_cfg.yaml -s http://schema.databio.org/refgenie/refgenie_build.yaml

Deploying assets onto the server

Setup

In this guide we'll use environment variables to keep track of where stuff goes.

• BASEDIR points to our parent folder where we'll do all the building/archiving
• GENOMES points to pipeline output (referenced in the project config)
• REFGENIE_RAW points to a folder where the downloaded raw files are kept
• REFGENIE points to the refgenie config file
• REFGENIE_ARCHIVE points to the location where we'll store the actual archives

#export BASEDIR=$HOME/code/sandbox/refgenie_deploy
#export REFGENIE_RAW=$BASEDIR/refgenie_raw
export SERVERNAME=plantref
export BASEDIR=$PROJECT/deploy/$SERVERNAME
export GENOMES=$BASEDIR/genomes
export REFGENIE_RAW=/project/shefflab/www/refgenie_$SERVERNAME
export REFGENIE=$BASEDIR/$SERVERNAME/config/refgenie_config.yaml
export REFGENIE_ARCHIVE=$GENOMES/archive
mkdir $BASEDIR
cd $BASEDIR

To start, clone this repository:

git clone git@github.com:refgenie/$SERVERNAME.git

Step 1: Download input files

Many of the assets require some input files, and we have to make sure we have those files locally. In the recipe_inputs.csv file, we have entered these files as remote URLs, so the first step is to download them. We have created a subproject called getfiles for this: To programmatically download all the files required by refgenie build, run from this directory using looper:

cd $SERVERNAME
mkdir -p $REFGENIE_RAW
looper run asset_pep/refgenie_build_cfg.yaml -p local --amend getfiles

Check for errors here:

grep checksum ../genomes/submission/*.log

Step 2: Build assets

Once files are present locally, we can run refgenie build on each asset specified in the sample_table (assets.csv). If you have not initialized it, then first you must init the config:

refgenie init -c config/refgenie_config.yaml -f $GENOMES -u https://refgenie.s3.amazonaws.com -a $GENOMES/archive -b refgenie_config_archive.yaml

We have to submit fasta assets first:

looper run asset_pep/refgenie_build_cfg.yaml -p bulker_slurm --sel-attr asset --sel-incl fasta

This will create one job for each asset. Monitor job progress with:

looper check asset_pep/refgenie_build_cfg.yaml  # TODO: this doesn't work because the pipeline doesn't produce flags...

grep CANCELLED ../genomes/submission/*.log
ll ../genomes/submission/*.log
grep error ../genomes/submission/*.log
grep maximum ../genomes/submission/*.log

ll ../genomes/data/*/*/*/_refgenie_build/*.flag
ll ../genomes/data/*/*/*/_refgenie_build/*failed.flag
ll ../genomes/data/*/*/*/_refgenie_build/*completed.flag
ll ../genomes/data/*/*/*/_refgenie_build/*running.flag
ll ../genomes/data/*/*/*/_refgenie_build/*completed.flag | wc -l
cat ../genomes/submission/*.log

To run all the asset types:

looper run asset_pep/refgenie_build_cfg.yaml -p bulker_slurm

Step 3. Archive assets

Assets are built locally now, but to serve them, we must archive them using refgenieserver. The general command is refgenieserver archive -c <path/to/genomes.yaml>. Since the archive process is generally lengthy, it makes sense to submit this job to the cluster. We can use looper to that. To start over completely, remove the archive config file with: rm config/refgenie_config_archive.yaml

looper run asset_pep/refgenieserver_archive_cfg.yaml -p bulker_slurm --sel-attr asset --sel-incl fasta --lumpn 5

<!-- looper run asset_pep/refgenieserver_archive_cfg.yaml -p slurm -t 0.1 -c partition=standard -->

Check progress with:

ll ../genomes/archive_logs/submission/*.log
grep Wait ../genomes/archive_logs/submission/*.log
grep Error ../genomes/archive_logs/submission/*.log
cat ../genomes/archive_logs/submission/*.log

Now the archives should be built, so we'll sync them to AWS. Use the refgenie credentials (here added with --profile refgenie, which should be preconfigured with aws configure)

aws s3 sync $REFGENIE_ARCHIVE s3://awspds.refgenie.databio.org --profile refgenie

Step 4. Deploy server

Now everything is ready to deploy. If using refgenieserver directly, you'll run refgenieserver serve config/refgenieserver_archive_cfg. We're hosting this repository on AWS and use GitHub Actions to trigger trigger deploy jobs to push the updates to AWS ECS whenever a change is detected in the config file.

ga -A; gcm "Deploy to ECS"; gpoh