XAR Files

2024-03-28

Experiment description or XAR (eXperimental ARchive ) files contain XML files that describe an experiment as a series of steps performed on specific inputs, producing specific outputs. The metadata objects are identified by Life Science Indentifiers (LSIDs).

A LabKey XAR file is a ZIP archive with a renamed file extension. It is not to be confused with other files that use the same .xar file extension but are used for different purposes including "extensible archiver" and "extensible archive format".

At the root of a LabKey XAR file is a xar.xml file that serves as a manifest for the contents of the XAR. A .xar.xml file can also be imported directly, without being packaged into a wrapped .xar file.

The topics in this section explain the xar.xml structure and walk through several specific examples. After working through these examples, readers should be able to begin authoring xar.xml files to describe their own experiments. You can author new xar.xml files in an XML editor.

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Uses of XAR Files

Describing an experiment in a xar.xml file is one way to enable the export and import of experimental results. The granularity of experimental procedure descriptions, how data sets are grouped into runs, and the types of annotations attached to the experiment description are all up to the author of the xar.xml. The appropriate answers to these design decisions depend on the uses intended for the experiment description.If this is the author's sole purpose, the description can be minimal—a few broadly stated steps.

The experiment framework also serves as a place to record lab notes so that they are accessible through the same web site as the experimental results. It allows reviewers to drill in on the question, "How was this result achieved?" This use of the experiment framework is akin to publishing the pages from a lab notebook. When used for this purpose, the annotations can be blocks of descriptive text attached to the broadly stated steps.

A more ambitious use of experiment descriptions is to allow researchers to compare results and procedures across whatever dimensions they deem to be relevant. For example, the framework would enable the storage and comparison of annotations to answer questions such as:

  • What are all the samples used in our lab that identified protein X with an expectation value of Y or less?
  • How many samples from mice treated with substance S resulted in an identification of protein P?
  • Does the concentration C of the reagent used in the depletion step affect the scores of peptides of type T?
In order to turn these questions into unambiguous and efficient queries to the database, the attributes in question need to be clearly specified and attached to the correct element of the experiment description.

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