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Parse the genetic return of results XML report from GeneInsight into a relational database.

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GeneInsight XML Parser for eMerge Network

This code parses the genetic return of results XML report from GeneInsight into a relational database.

The XML file is parsed into 8 tables. The Report table is the main table and represents the root of the XML file. The other 7 tables represent nodes that can have one or more children in the XML file.

Tables:

  • Report
  • InterpretedDiseases
  • PatientDiseases
  • ReportAssays
  • ReportVariants
  • NestedVariants
  • Specimens
  • Physicians

Instructions:

  • Modify config_example.ini to include your database connection. This value will include the server name, database, your username, and password. Go to this site for more information on
    configuring sqlalchemy for MSSQL, MySQL, Postgres, etc.
  • Rename config_example.ini to config.ini
  • Run this command to parse the file and insert it into you database:
    python parse_xml_file.py report.xml

The tables will be created automatically, but you can also create the empty tables by using create_tables.py. More importantly, if the tables already exist, and you want to completely remove them and recreate them, use python create_tables.py drop. This is useful for initially testing the parser on your xml files.

Notes:

  • You will need to install python packages sqlalchemy and pyodbc.
  • In order to get pyodbc to work on mac (and probably linux), you need to install unixodbc and freetds. On Mac, these commands are:
    brew install unixodbc
    brew install freetds --with-unixodbc
  • An easy way to test without having to connect to a SQL database is to use SQLite. The default connection in the config_example.ini file is set to sqlite:///my_database.db which will create a database file in the current directory.





This research project was supported by the National Human Genome Research Institute, National Institutes of Health, through Grant U01HG008680. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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