Tuesday, 3 December 2013

File management for large SLiMSuite runs

The latest release of SLiMSuite features a slight modification to the way that files are generated and tidied, which can be beneficial for large runs.

Previously, a different results directory (resdir=PATH) was required for each different run to avoid dataset-specific results being over-written. The partial exception was the *.pickle.gz file, which included some SLiMBuild information in its name. (This is predominantly to speed up the ability of (Q)SLiMFinder to recognise when an intermediate pickle file can be used or not.) As of the latest release, the RunID (runid=X) is also now included in dataset-specific output, allowing results from several different runs (with different RunIDs) to go into the same results directory.

The exception is the files that are created as part of the initial setup/SLiMBuild process: *.slimdb, *.dis.tdt and *.upc. From a given Dataset and RunID, the following files will therefore be generated in ResDir/


Note that the default ResDir is SLiMFinder/, QSLiMFinder/ or SLiMProb and the default RunID is the date and time of the run.

TarGZ and SaveSpace

Obviously, the results directory can quickly fill up with files if there are multiple datasets and/or runs with different RunIDs. The way to get round this is to use the targz=T and savespace=X options.

targz=T will package up all of the files associated with a specific run into a single Dataset.RunID.tgz file. This does not work on Windows. (Note that previous versions generated a Dataset.tar.gz file.) The *.pickle.gz file associated with the run will not be included in the tar file unless savespace=2+ (see below).

Note: the tar file is actually generated from the run directory, not the results directory and will include the relative path to ResDir in the tarred files. This means that if you enter ResDir/ and then tar -xzf Dataset.RunID.tgz, an additional ResDir/ will be created in which the files can be found. This is actually pretty useful as it allows the user to unpack individual runs and then delete the whole directory when finished. To return individual results to their “rightful” place, simply run the tar command from the same directory that the SLiMSuite program was run from (e.g. tar -xzf ResDir/Dataset.RunID.tgz).

The savespace=X option saves space by deleting excess files. It is strongly recommended that this is used in conjunction with the targz=T. There are now four levels of savespace=X:

  • 0 = Delete no files
  • 1 = Delete all bar *.upc and *.pickle (Pickle excluded from tar.gz with this setting)
  • 2 = Delete all bar *.upc files (Pickle included in tar.gz with this setting)
  • 3 = Delete all dataset-specific files including *.upc and *.pickle (not *.tar.gz)

Another way to think of this is that 0 will delete nothing, 1 will leave enough files to rerun the same dataset/SLiMBuild combination, 2 will leave enough to run the same dataset with additional SLiMBuild settings, whilst 3 will cleanup absolutely everything.

The recommended setting for running on a cluster or supercomputer is targz=T savespace=1 unless file numbers are an issue, in which case targz=T savespace=2 would be better. targz=T savespace=3 is only really recommended when you are confident that all datasets will run to completion without issues. If there is a chance of nodes going down or walltimes being reached, it is better to keep the pickle files accessible for re-runs.

New downloads and fixed webpages

New releases of SeqSuite and SLiMSuite are now available. The webpages have now hopefully been fixed too, including the broken Manual links. (A bit of trouble parsing some the docstrings had messed up the HTML, in case you care!) Please report any more anomalies.

There are not many major updates since the last release. The biggest are that SLiMFinder (and QSLiMFinder) now produce a single *.occ.csv containing motif instances for all datasets, in addition to the old dataset-specific files. This is to make the output more consistent with SLiMProb although do note that some of the column headers are different. The new file contains the same data as the old dataset-specific *.occ.csv files plus two additional columns: Dataset and RunID. (These match the main *.csv output.)

Dataset-specific results files have also been cleaned up a little for (Q)SLiMFinder and SLiMProb (i.e. the SLiMCore Class in libraries/rje_slimcore) to make the targz=T/F and savespace=X options a little more useful and consistent. This will be the subject of another post shortly.

Other miscellaneous updates are listed below.

Updates since last release:

• comparimotif_V3: Updated from Version 3.10.
→ Version 3.10: Added forking.
→ Version 3.11: Added additional overlap/matchfix checks during basic comparison to try and speed up.

• qslimfinder: Updated from Version 1.6.
→ Version 1.7: Fixed "MustHave=LIST" correction of motif space.

• slimfinder: Updated from Version 4.5.
→ Version 4.6: Minor modification to seqocc=T function. !Experimental! Added main occurrence output and modified savespace.

• rje_pydocs: Updated from Version 2.8.
→ Version 2.8: Added docsource=PATH : Input path for Python Module documentation (manuals etc.) ['../docs/']
→ Version 2.9: Attempts to fix some broken links and sort out manuals confusion

• rje_slimcore: Updated from Version 1.12.
→ Version 1.13: Modified the savespace settings to reduce numbers of files. targz file now uses RunID not Build Info.

• rje_uniprot: Updated from Version 3.14.
→ Version 3.14: Added dblist=LIST and dbsplit=T/F for additional DB link output control. Set unipath default to url.
→ Version 3.15: Added extraction of taxonomic groups. Add UniFormat to improve pure downloads.