How to find and work with Solve-RD data on Fender

First: getting an account and starting a session on a User Interface (UI) server

In order to work with Slurm and manage jobs on the cluster you'll need a personal account and start a session on a User Interface (UI) server. If you are completely new here, please:

1. Using the EGA FUSE client.

Solve-RD samples are read-only available on Fender via the EGA FUSE client. This client uses the File system in USErspace (FUSE) framework to make the Solve-RD data available as if it was located on just another disk. Hence the client will handle both transfer and on the fly decryption of the data. The data is located at the following mount point (path):


From there samples can be staged to /groups/${group}/tmp*/... for analysis.

Staging means copying a batch of data from the original location on prm storage to tmp storage, which is required as the prm storage is only available on the User Interface (UI) whereas tmp is also mounted on the compute nodes. See Keep - What is stored where on Fender for details on the differences between various storage systems. The total Solve-RD data set is huge: Don't try to stage all data simultaneously on a tmp file system:

  • It won't fit on the storage system and
  • Is useless anyway as there is not a single cluster node that can possibly analyse all samples in a single job

Select a reasonable batch size instead, stage and process those samples, use rigorous QC and when the rsults are Ok, make a release / data freeze for the results, which can then be moved to a prm file system for longer term storage followed by cleanup from tmp to free up space for a next batch.

Unfortunately the EGA FUSE client is not so fast, so you may prefer to use the EGA FUSE client client only to lookup which data is available from which paths and then do the staging of large files using the EGA Python API with pyEGA3 (see below).

2. Using the EGA Python API with pyEGA3.

To be able to use pyEGA3 you need a username and password provided by the EGA. These EGA credentials are not the same as your account for the Fender cluster and must be requested separately.

Add your credentials into a credentials.json file, which is then used during data transfer. An example of the syntax for this credentials.json file is located in the PyEGA3 repository at GitHub. For more on PyEGA3 see the example code snippets below and the in the root of the repo.

Example for downloading all files corresponding to specific sample from an EGA data set accession number.

echo 'Loading module pyEGA3 ...'
module load pyEGA3


mkdir -p -v "${outputdir}"

echo "Looking up all sampleIDs for data set ${ega_data_set_accession} and storing them into a ${ega_data_set_accession}.tmp file ..."
pyega3 -cf credentials.json files "${ega_data_set_accession}" > "${ega_data_set_accession}.tmp"

echo "Lookup all EGA file accession numbers corresponding to sample ID ${sample_id} ..."
grep "${sample_id}" "${ega_data_set_accession}.tmp" | awk '{print $1}' >> "${sample_id}.tmp"

echo "Staging all files for sample ${sample} to "${output_dir}" ..."
for ega_file_accession in $(cat "${sample_id}.tmp")
    pyega3 -cf credentials.json -c 10 fetch "${ega_file_accession}" --saveto "${output_dir}"

Or see more extended examples here: /groups/solve-rd/prm*/example_scripts