HML is Histocompatibility Markup Language, an XML-style document used to communicate HLA Genotyping results. The format is described at schemas.nmdp.org and the workshop database supports HML version 1.0.1. These files are validated for consistency with the XML Schema, and according to MIRING specifications and the NMDP Gateway.
Specific guidelines for vendors have been developed regarding the generation of HML documents for the workshop, as well as the selection of relevant reference sequences. More information on this is available on the IHIW github page.
HML Documents can be exported from several vendor software packages, specific instructions below:
1) File ->Custom Export -> Configure custom exports
2) on [Exporting] tab click [New]
3) Select [Type] = HML version 1.0
4) Assign a Name (ex. “IHIW HML”)
After the export format is setup, then you can create an export
1) File -> Custom Export -> IHIW HML
2) Find the HML file in the /Exports folder
3) Possibly: Upload to the IHIW database and check the validation statuses
- To generate the HML in Assign: Following usual sample import and analysis, in the Assign interface click Generate then the HML tab.
- Select “Modify Additional Information” which will allow the user to input data into the Additional Information boxes (Project Name, Reporting Center ID, etc.) These boxes are required and must be filled in.
- Click Update which will enter and save this information into the Assign settings file so the user does not have to re-enter each time they generate an HML file, unless they choose to. Click Generate Report and navigate to the desired folder in which to save the HML file. Click Done.
One Lambda Thermofisher (Coming Soon)
Omixon (Coming Soon)
Immucor (Coming Soon)
HML files that are updated to the IHIW18 database are validated for three things:
- Valid HML Schema
- MIRING specifications
- NMDP Gateway Validation
Please note that “invalid” data sets are probably still usable. Users are encouraged to upload data even if there are validation issues, the validation feedback is intended to be helpful, it’s not indicating that the data is rejected. Many validation issues can be overcome as data is more closely analyzed.