{ "info": { "author": "Gijs Kant", "author_email": "gijs@thehyve.nl", "bugtrack_url": null, "classifiers": [ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Topic :: Scientific/Engineering :: Bio-Informatics" ], "description": "CSR to TranSMART loader\n=======================\n\n|Build status| |codecov| |pypi| |status| |license|\n\n.. |Build status| image:: https://travis-ci.org/thehyve/python_csr2transmart.svg?branch=master\n :alt: Build status\n :target: https://travis-ci.org/thehyve/python_csr2transmart/branches\n.. |codecov| image:: https://codecov.io/gh/thehyve/python_csr2transmart/branch/master/graph/badge.svg\n :alt: codecov\n :target: https://codecov.io/gh/thehyve/python_csr2transmart\n.. |pypi| image:: https://img.shields.io/pypi/v/csr2transmart.svg\n :alt: PyPI\n :target: https://pypi.org/project/csr2transmart/\n.. |status| image:: https://img.shields.io/pypi/status/csr2transmart.svg\n :alt: PyPI - Status\n.. |license| image:: https://img.shields.io/pypi/l/csr2transmart.svg\n :alt: MIT license\n :target: LICENSE\n\nThis package contains a script that transforms Central Subject Registry data to a format\nthat can be loaded into the TranSMART_ platform,\nan open source data sharing and analytics platform for translational biomedical research.\n\nThe output of the transformation is a collection of tab-separated files that can be loaded into\na TranSMART database using the transmart-copy_ tool.\n\n.. _TranSMART: https://github.com/thehyve/transmart-core\n.. _transmart-copy: https://github.com/thehyve/transmart-core/tree/dev/transmart-copy\n\n\u26a0\ufe0f Note: this is a very preliminary version, still under development.\nIssues can be reported at https://github.com/thehyve/python_csr2transmart/issues.\n\n\nInstallation and usage\n**********************\n\nTo install csr2transmart, do:\n\n.. code-block:: console\n\n pip install csr2transmart\n\nor from sources:\n\n.. code-block:: console\n\n git clone https://github.com/thehyve/python_csr2transmart.git\n cd python_csr2transmart\n pip install .\n\n\nData model\n----------\n\nThe Central Subject Registry (CSR) data model contains individual,\ndiagnosis, biosource and biomaterial entities. The data model is defined\nas a data class in `csr/csr.py`_\n\n.. _`csr/csr.py`: https://github.com/thehyve/python_csr2transmart/blob/master/csr/csr.py\n\nTo learn how to add changes to the database model, see `changing-data-model.rst`_ document.\n\n.. _`changing-data-model.rst`: https://github.com/thehyve/python_csr2transmart/blob/master/changing-data-model.rst\n\n\nUsage\n------\n\nThis repository contains a number of command line tools:\n\n* ``sources2csr``: Reads from source files and produces tab delimited CSR files.\n* ``csr2transmart``: Reads CSR files and transforms the data to the TranSMART data model,\n creating files that can be imported to TranSMART using `transmart-copy`.\n* ``csr2cbioportal``: Reads CSR files and transforms the data to patient and sample files\n to imported into cBioPortal.\n\n``sources2csr``\n~~~~~~~~~~~~~~~\n\n.. code-block:: console\n\n sources2csr \n\nThe tool reads input files from ```` and\nwrites CSR files in tab-delimited format (one file per entity type) to\n````.\nThe output directory ```` needs to be either empty or not yet existing.\n\nThe sources configuration will be read from ``/sources_config.json``,\na JSON file that contains the following attributes:\n\n* ``entities``: a map from entity type name to a description of the sources for that entity type. E.g.,\n\n .. code-block:: json\n\n {\n \"Individual\": {\n \"attributes\": [\n {\n \"name\": \"individual_id\",\n \"sources\": [\n {\n \"file\": \"individual.tsv\",\n \"column\": \"individual_id\"\n }\n ]\n },\n {\n \"name\": \"birth_date\",\n \"sources\": [\n {\n \"file\": \"individual.tsv\",\n \"date_format\": \"%d-%m-%Y\"\n }\n ]\n }\n ]\n }\n }\n\n The entity type names have to match the entity type names in the CSR data model and\n the attribute names should match the attribute names in the data model as well.\n The ``column`` field is optional, by default the column name is assumed to be\n the same as the attribute name.\n For date fields, a ``date_format`` can be specified. If not specified, it is\n assumed to be ``%Y-%m-%d`` or any other `date formats supported by Pydantic`_.\n If multiple input files are specified for an attribute, data for that attribute\n is read in that order, i.e., only if the first file has no data for an attribute\n for a specific entity, data for that attribute for that entity is read from the next file, etc.\n\n* ``codebooks``: a map from input file name to codebook file name, e.g., ``{\"individual.tsv\": \"codebook.txt\"}``. \n Naming convention: _codebook.txt\n\n* ``file_format``: a map from input file name to file format configuration,\n which allows you to configure the delimiter character (default: ``\\t``).\n E.g., ``{\"individual.tsv\": {\"delimiter\": \",\"}}``.\n\nSee `test_data/input_data/config/sources_config.json`_ for an example.\n\nContent of the codebook files has to match the following format:\n\n* First a header line with a number and column names the codes apply to. \n The first field has a number, the second field a space separated list of column names, e.g., ``1\\tSEX GENDER``.\n* The lines following the header start with an empty field. \n Then the lines follow the format of ``code\\tvalue`` until the end of the line, \n e.g., ``\\t1\\tMale\\t2\\tFemale``.\n* The start of a new header, which is detected by the first field not being empty \n starts the process over again.\n\nSee ``_ for a codebook file example.\n\n.. _`date formats supported by Pydantic`: https://pydantic-docs.helpmanual.io/#datetime-types\n.. _`test_data/input_data/config/sources_config.json`: https://github.com/thehyve/python_csr2transmart/blob/master/test_data/input_data/config/sources_config.json\n\n\n``csr2transmart``\n~~~~~~~~~~~~~~~~~\n\n.. code-block:: console\n\n csr2transmart \n\nThe tool reads CSR files from ```` (one file per entity type),\ntransforms the CSR data to the TranSMART data model. \nIn addition, if there is ``--ngs-dir`` specified,\nthe tool will read the NGS files inside to determine values of additional CSR biomaterial variables.\nThe tool writes the output in ``transmart-copy`` format to ````.\nThe output directory ```` needs to be either empty or not yet existing.\n\nThe ontology configuration will be read from ``/ontology_config.json``.\nSee `test_data/input_data/config/ontology_config.json`_ for an example.\n\n.. _`test_data/input_data/config/ontology_config.json`: https://github.com/thehyve/python_csr2transmart/blob/master/test_data/input_data/config/ontology_config.json\n\n\n``csr2cbioportal``\n~~~~~~~~~~~~~~~~~~\n\n.. code-block:: console\n\n csr2cbioportal [--ngs-dir ] \n\nThe tool reads CSR files from ```` (one file per entity type),\nand optionally NGS data (genomics data) from ````,\ntransforms the CSR data to the clinical data format for cBioPortal and\nwrites the following data types to ````:\n\n* Clinical data \n* Mutation data\n* CNA Segment data\n* CNA Continuous data\n* CNA Discrete data\n\nFile structure, case lists and meta files will also be added to the output folder.\nSee the `cBioPortal file formats`_ documentation for further details.\n\nThe output directory ```` needs to be either empty or not yet existing.\n\n.. _`cBioPortal file formats`: https://docs.cbioportal.org/5.1-data-loading/data-loading/file-formats\n\nSource data assumptions and validation\n--------------------------------------\n\nGeneral file characteristics\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n* ``Delimiter`` The source data should be provided as delimited text files. The delimiter can be `configured`_ per \n data file. If not configured, a tab-delimited file is assumed.\n* ``Comments`` Comment lines may be present, indicated by a ``#`` as the first character. These lines will be ignored.\n* ``Header`` The first non-comment line is assumed to be the header. It should be exactly one line.\n* ``Field number`` The number of fields (columns) is determined by the header. Every other line in the file \n should have this same number of fields (no blank lines).\n* ``Whitespace`` Leading or trailing whitespace is not trimmed. If present, it will persist in the final observation.\n* ``Encoding`` All files are assumed to be utf-8 encoded.\n\nCSR entities\n~~~~~~~~~~~~\n\nAll characteristics and relationships of the CSR data model are defined in `csr/csr.py`_. Any field present in the\nsource data that you would like to load to tranSMART, must be linked to a CSR field via the sources_config. Additional\nfields not present in the sources_config will be ignored.\n\nRegarding the source data, we can distinguish four types of validation:\n\n1. ``Value validation`` Independent validation of a single field value. This comprises type validation (e.g. string, integer or date), nullability (whether a field may be empty), and unique constraints.\n2. ``Record validation`` Validation across different fields from the same record within the same entity. This validation is relevant when the validity of a field value is dependent on the other fields of the same record (e.g. a biosource record with src_biosource_id = BS1, is invalid when biosource_id = BS1).\n3. ``Entity validation`` Concerns the integrity check of all records within a single entity (e.g. do all src_biosource_id values also have corresponding biosource_id records within the biosource entity).\n4. ``Across-entity validation`` Checks the validity of relationships between records of different entities.\n\nThe data validation of the current pipeline is implemented for type 1 and to a limited extent for type 2 and 4.\nHence, the source data is assumed to be coherent regarding its relationships within the same entity and across\ndifferent entities. While most erroneous relationships across entities, in respect of missing entity records, will be\ndetected (e.g. a biomaterial linked to a non-existing biosource), logically impossible relationships are not (e.g.\nbiomaterial BM2 is derived from BM1, but from a different biosource).\n\nAll entities must have a link to an individual, either through their individual-referencing field\nor through a reference to an entity of other type that has an individual-referencing field.\nOtherwise an error will be thrown.\n\nAdditionally, any individual needs to have at least one observation to be included.\nThis means that merely a collection of related ID values, without observations\nlinked to any of those IDs, will not become available in tranSMART.\n\n.. _`configured`: https://github.com/thehyve/python_csr2transmart/blob/master/test_data/input_data/config/sources_config.json#L390\n\n\nNGS data\n~~~~~~~~\n\nAll NGS data should follow reference genome HG38.\nThe sample ID is structured as _,\nbased on the IDs of biosources and biomaterials from clinical data, e.g. PMCBS000AAA_PMCBM000AAA.\n\nThe naming conventions for NGS input data are as follows:\n\n- mutation data (Small nucleotide variants): .maf.gz\n- Segment data: .seg\n- Continuous CNA per gene: _all_data_by_genes.txt\n- Discrete CNA per gene: _all_thresholded.by_genes.txt\n\nMultiple files per type are supported. Note that mutation files must be always compressed as ``maf.gz``. See the `NGS test data`_ for an example.\n\nEach of the NGS file names can contain the optional string '_WGS' or '_WSX' to indicate the NGS analysis type, e.g. _WXS_all_data_by_genes.txt. If present, each sample in the NGS file will be associated with the corresponding value for the derived variable ``analysis_strategy``. String mapping rules are encoded in `ngs_reader.py`_.\n\nAdditionally, the derived variable ``library_strategy`` is generated for each sample based on the NGS file extension. See specific NGS reader scripts in `sources2csr`_ for mapping rules between file type and and library strategy.\n\nBoth derived variables are associated to the entity Biomaterial in TranSMART (see `ngs2csr.py`_); to have them appear in the TranSMART ontology tree after data loading, you need to include them in `ontology_config.json`_, e.g.:\n\n.. code-block:: json\n\n {\n \"name\": \"Biomaterial information\",\n \"children\": [\n {\n \"name\": \"Library strategy\",\n \"concept_code\": \"Biomaterial.library_strategy\"\n },\n {\n \"name\": \"Analysis type\",\n \"concept_code\": \"Biomaterial.analysis_type\"\n }\n ]\n }\n\n.. _`NGS test data`: https://github.com/thehyve/python_csr2transmart/blob/master/test_data/input_data/CSR2CBIOPORTAL_TEST_DATA/NGS\n.. _`ngs_reader.py`: https://github.com/thehyve/python_csr2transmart/blob/master/sources2csr/ngs_reader.py\n.. _`sources2csr`: https://github.com/thehyve/python_csr2transmart/blob/master/sources2csr\n.. _`ngs2csr.py`: https://github.com/thehyve/python_csr2transmart/blob/master/sources2csr/ngs2csr.py#L54\n.. _`ontology_config.json`: https://github.com/thehyve/python_csr2transmart/blob/master/test_data/input_data/config/ontology_config.json\n\n\nPython versions\n---------------\n\nThis package supports Python versions 3.7 - 3.10.\n\n\nPackage management and dependencies\n-----------------------------------\n\nThis project uses `pip` for installing dependencies and package management.\n\n* Dependencies should be added to `requirements.txt`_.\n\n.. _`requirements.txt`: https://github.com/thehyve/python_csr2transmart/blob/master/requirements.txt\n\nTesting and code coverage\n-------------------------\n\n* Tests are in the ``tests`` folder.\n\n* The ``tests`` folder contains tests for each of the tools and\n a test that checks whether your code conforms to the Python style guide (PEP 8) (file: ``test_lint.py``)\n\n* The testing framework used is `PyTest `_\n\n* Tests can be run with ``python setup.py test``\n\nCoding style conventions and code quality\n-----------------------------------------\n\n* Check your code style with ``prospector``\n\n* You may need run ``pip install .[dev]`` first, to install the required dependencies\n\n\nLicense\n*******\n\nCopyright (c) 2019 The Hyve B.V.\n\nThe CSR to TranSMART loader is licensed under the MIT License. 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