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Added cit pipline tutorial and updated documentation
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WassimG committed Oct 10, 2024
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4 changes: 1 addition & 3 deletions .gitignore
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# output files in tutorials folder
tutorials/
!tutorials/Oktoberfest Tutorial.ipynb
!tutorials/Oktoberfest_workshop.ipynb
!tutorials/*.ipynb

# example data
data/
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4 changes: 4 additions & 0 deletions docs/_static/custom_cookietemple.css
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padding-left: 50px;
}

.ptm-config-table tbody tr:not(:first-child) td:nth-child(1) {
padding-left: 50px;
}

.lib-refinement-learning-config-table
tbody
tr:nth-child(n + 2):nth-child(-n + 5)
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30 changes: 25 additions & 5 deletions docs/config.rst
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Expand Up @@ -147,17 +147,37 @@ Applicable to in-silico digestion
| db | Defines whether the digestion should contain only targets, only decoys or both (concatenated); can be "target", "decoy" or "concat"; default = "concat" |
+----------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------+

Applicable to PTM pipeline
---------------------------------

.. table::
:class: fixed-table ptm-config-table

+----------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Parameter | Description |
+============================+====================================================================================================================================================================+
| ptm_localization | Flag to indicate whether the user want to run the PTM localization pipeline or not. |
+----------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ptmLocalizationOptions | Contains specific settings for the ptm pipele (see following 2 nested parameters) |
+----------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| unimod_id | unimod_id from unimod.org to indicate the target ptm. e.g (7 for citrullination/deamidation) |
+----------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| possible_sites | List of Possible sites where the PTM can happen. e.g (['R','N','Q'] for citrullination/deamidation) |
+----------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| neutral_loss | Flag to annotate neutral loss peaks or not. |
+----------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------+

Applicable to local intensity prediction
----------------------------------------

.. table::
:class: fixed-table

+--------------------------+---------------------------------------------------+
| Parameter | Description |
+==========================+===================================================+
| dlomixInferenceBatchSize | Batch size to use for local inference with DLomix |
+--------------------------+---------------------------------------------------+
+----------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Parameter | Description |
+============================+====================================================================================================================================================================+
| dlomixInferenceBatchSize | Batch size to use for local inference with DLomix |
+----------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------+

Applicable to transfer/refinement learning
------------------------------------------
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