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The jmzQuantML programming interface and validator for the mzQuantML data standard.

Qi D, Krishna R, Jones AR - Proteomics (2014)

Bottom Line: The mzQuantML standard from the HUPO Proteomics Standards Initiative has recently been released, capturing quantitative data about peptides and proteins, following analysis of MS data.We present a Java application programming interface (API) for mzQuantML called jmzQuantML.The API provides robust bridges between Java classes and elements in mzQuantML files and allows random access to any part of the file.

View Article: PubMed Central - PubMed

Affiliation: Institute of Integrative Biology, University of Liverpool, UK.

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Diagram of the steps for marshalling and unmarshalling mzQuantML files using the jmzQuantML API, 250 × 129 mm (300 × 300 DPI).
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fig01: Diagram of the steps for marshalling and unmarshalling mzQuantML files using the jmzQuantML API, 250 × 129 mm (300 × 300 DPI).

Mentions: We have generated some example code to demonstrate how to use jmzQuantML for marshalling and unmarshalling mzQuantML files, which is available from http://code.google.com/p/jmzquantml/w/list. The API implements two main functions for mzQuantML files: marshalling and unmarshalling. Marshalling is the process of writing Java objects as XML fragments to an mzQuantML file stored on the disk, whereas unmarshalling is the reverse—reading XML fragments from an mzQuantML file into memory as Java objects. These functions are provided as two main classes: MzQuantMLMarshaller and MzQuantMLUnmarshaller. These classes provide more than one way of performing marshalling and unmarshalling operations in order to give more flexibility to users. Figure 1 illustrates the work-flow of marshalling and unmarshalling. Marshalling an mzQuantML object to a file is more straightforward than unmarshalling. The user first creates an MzQuantMLMarshaller object, then must follow one of two different paths: via the MzQuantML object (Path A in the Marshall flowchart in Fig. 1) or FileWriter (Path B in Fig. 1). Path A requires the user to create an empty MzQuantML object as the root element to which all other element objects are attached. The element objects are generated by the JAXB compiler directly from the mzQuantML schema definition file. Each element object provides setter and getter methods for populating data into correct and valid attribute types. The relationship between the mzQuantML elements and the Java objects is illustrated in Fig. 2. All the required element objects are added to the root object before marshalling the whole object to an mzQuantML file. This method is only recommended for marshalling small files, as the entire object tree becomes loaded into memory. For large file, API users are recommended to follow the FileWriter method (Path B). By using a FileWriter, no memory issues occur and files of almost any size can be produced. The marshalling process in Path B functions via writing each required blocks of elements direct to file, for example the process starts by writing a start tag (MzQuantMLMarshaller.createMzQuantMLStartTag) and finishes by writing closing tag (MzQuantMLMarshaller.createMzQuantMLClosingTag). This method for file writing requires API users to be aware of the order of elements that must be written to create a valid mzQuantML file. The recommended order can be found inspecting the mzQuantML XML Schema. For jmzQuantML users following Path A, the order of element writing is not important.


The jmzQuantML programming interface and validator for the mzQuantML data standard.

Qi D, Krishna R, Jones AR - Proteomics (2014)

Diagram of the steps for marshalling and unmarshalling mzQuantML files using the jmzQuantML API, 250 × 129 mm (300 × 300 DPI).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4016760&req=5

fig01: Diagram of the steps for marshalling and unmarshalling mzQuantML files using the jmzQuantML API, 250 × 129 mm (300 × 300 DPI).
Mentions: We have generated some example code to demonstrate how to use jmzQuantML for marshalling and unmarshalling mzQuantML files, which is available from http://code.google.com/p/jmzquantml/w/list. The API implements two main functions for mzQuantML files: marshalling and unmarshalling. Marshalling is the process of writing Java objects as XML fragments to an mzQuantML file stored on the disk, whereas unmarshalling is the reverse—reading XML fragments from an mzQuantML file into memory as Java objects. These functions are provided as two main classes: MzQuantMLMarshaller and MzQuantMLUnmarshaller. These classes provide more than one way of performing marshalling and unmarshalling operations in order to give more flexibility to users. Figure 1 illustrates the work-flow of marshalling and unmarshalling. Marshalling an mzQuantML object to a file is more straightforward than unmarshalling. The user first creates an MzQuantMLMarshaller object, then must follow one of two different paths: via the MzQuantML object (Path A in the Marshall flowchart in Fig. 1) or FileWriter (Path B in Fig. 1). Path A requires the user to create an empty MzQuantML object as the root element to which all other element objects are attached. The element objects are generated by the JAXB compiler directly from the mzQuantML schema definition file. Each element object provides setter and getter methods for populating data into correct and valid attribute types. The relationship between the mzQuantML elements and the Java objects is illustrated in Fig. 2. All the required element objects are added to the root object before marshalling the whole object to an mzQuantML file. This method is only recommended for marshalling small files, as the entire object tree becomes loaded into memory. For large file, API users are recommended to follow the FileWriter method (Path B). By using a FileWriter, no memory issues occur and files of almost any size can be produced. The marshalling process in Path B functions via writing each required blocks of elements direct to file, for example the process starts by writing a start tag (MzQuantMLMarshaller.createMzQuantMLStartTag) and finishes by writing closing tag (MzQuantMLMarshaller.createMzQuantMLClosingTag). This method for file writing requires API users to be aware of the order of elements that must be written to create a valid mzQuantML file. The recommended order can be found inspecting the mzQuantML XML Schema. For jmzQuantML users following Path A, the order of element writing is not important.

Bottom Line: The mzQuantML standard from the HUPO Proteomics Standards Initiative has recently been released, capturing quantitative data about peptides and proteins, following analysis of MS data.We present a Java application programming interface (API) for mzQuantML called jmzQuantML.The API provides robust bridges between Java classes and elements in mzQuantML files and allows random access to any part of the file.

View Article: PubMed Central - PubMed

Affiliation: Institute of Integrative Biology, University of Liverpool, UK.

Show MeSH