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YCGA Sequence Data Archive

Retrieve Data from the Archive

In the sequencing archive on Ruddle, a directory exists for each run, holding one or more tar files. There is a main tar file, plus a tar file for each project directory. Most users only need the project tar file corresponding to their data.

Although the archive actually exists on tape, you can treat it as a regular directory tree. Many operations such as ls, cd, etc. are very fast, since directory structures and file metadata are on a disk cache. However, when you actually read the contents of files the tape is mounted and the file is read into a disk cache.

Archived runs are stored in the following locations.

Original location Archive location
/panfs/sequencers /SAY/archive/YCGA-729009-YCGA/archive/panfs/sequencers
/ycga-ba/ba_sequencers /SAY/archive/YCGA-729009-YCGA/archive/ycga-ba/ba_sequencers
/gpfs/ycga/sequencers/illumina/sequencers /SAY/archive/YCGA-729009-YCGA/archive/ycga-gpfs/sequencers/illumina/sequencers

You can directly copy or untar the project tarfile into a scratch directory.

cd ~/scratch60/somedir
tar –xvf /SAY/archive/YCGA-729009-YCGA/archive/path/to/file.tar

Inside the project tar files are the fastq files, which have been compressed using quip. If your pipeline cannot read quip files directly, you will need to uncompress them before using them.

module load Quip
quip –d M20_ACAGTG_L008_R1_009.fastq.qp

For your convenience, we have a tool, restore, that will download a tar file, untar it, and uncompress all quip files.

module load ycga-public
restore –t /SAY/archive/YCGA-729009-YCGA/archive/path/to/file.tar

If you have trouble locating your files, you can use the utility locateRun, using any substring of the original run name. locateRun is in the same module as restore.

locateRun C9374AN

Restore spends most of the time running quip. You can parallelize and thereby speed up that process using the -n flag.

restore –n 20 ...


When retrieving data, run untar/unquip as a job on a compute node, not a login node and make sure to allocate sufficient resources to your job, e.g. –c 20 --mem=100G.


The ycgaFastq tool can also be used to recover archived data. See here.

Last update: May 27, 2022