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--- | ||
title: Housekeeping | ||
--- | ||
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Recurring "housekeeping" functions are provided by dedicated scripts with | ||
eponymoys functionality located in the `housekeepers` directory (e.g. `deleteAnalyses.py` | ||
is used for deleting records from teh `analyses` collection; `deleteBiosamplesWDS.py` | ||
deletes analyses and their downtream records - _i.e._ the associated analyses and | ||
the variants from those analyses). Additionally there is a separate `housekeeping.py` | ||
app for executing a number of standard maintenance functions in sequential order. | ||
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Functions for importing and updating (for now) reside in the separate `importers` directory. | ||
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## General Options | ||
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Most housekeepers (and other) apps have some general options: | ||
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* `--testMode true` will run a test setting, e.g. for deletion apps only indicate | ||
the numbers to be deleted w/o actually remving records | ||
- most destructive apps will fall back to test mode by default and ask for confirmation | ||
* `--limit 0` will perform the selected action on all records instad of a build-in | ||
default wherease e.g. `--limit 5` will just process a maximum of 5 records | ||
* `--force true` will perform the selected action even if there have been warnings | ||
or errors written to the pre-processor log file; onme is usually prompted for this | ||
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## Creating Collations - `collationsCreator.py` | ||
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The `collationsCreator` script updates the dataset specific `collations` collections | ||
which provide the aggregated data (sample numbers, hierarchy trees etc.) for all | ||
individual codes belonging to one of the entities defined in the `filter_definitions` | ||
in the `bycon` configuration. The (optional) hierarchy data is provided | ||
in `rsrc/classificationTrees/__filterType__/numbered-hierarchies.tsv` as a list | ||
of ordered branches in the format `code | label | depth | order`. | ||
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**TBD** The filter definition should be one of the configuration where users can | ||
provide additions and overrides in the `byconaut/local` directory. | ||
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### Arguments | ||
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* `-d`, `--datasetIds` ... to select the dataset (only one per run) | ||
* `--filters` ... to (optionally) limit the processing to a subset of samples | ||
(e.g. after a limited update) | ||
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### Use | ||
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* `bin/collationsCreator.py -d progenetix` | ||
* `bin/collationsCreator.py -d examplez --collationTypes "PMID"` | ||
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## Pre-computing Binned CNV Frequencies - `frequencymapsCreator` | ||
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This app creates the frequency maps for the "collations" collection. Basically, | ||
all samples matching any of the collation codes and representing CNV analyses | ||
are selected and the frequencies of CNVs per genomic bin are aggregated. The | ||
result contains teh gain and loss frquencies for all genomic intervals, for the | ||
given entity. | ||
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### Arguments | ||
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* `-d`, `--datasetIds` ... to select the dataset (only one per run) | ||
* `--collationTypes` ... to (optionally) limit the processing to a selected | ||
collation types (e.g. `NCIT`, `PMID`, `icdom` ...) | ||
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### Use | ||
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* `bin/frequencymapsCreator.py -d progenetix` | ||
* `bin/frequencymapsCreator.py -d examplez --collationTypes "icdot"` | ||
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## Deleting Records | ||
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Records are deleted by providing a standard pgx-style tab-delimited metadata file | ||
where only the corresponding `..._id` column is essential. As example, the | ||
`deleteIndividuals.py` app will take a table which includes a column `individual_id` | ||
and use these values to delete the matching records. |
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