MATLAB APPLICATION DEPLOYMENT - WEB EXAMPLE GUIDE Manuale Utente Scaricare il pdf (Pagina 19)

2. Under Programming Libraries in the right column, click the

zip link for the MATLAB library.

3. Download the zip file and unzip it into your

MATLAB7/toolboxes directory. If you do not have permission to

put files in that directory, unzip into any other directory.

4. After downloading and unzipping the files, add the directories to your MATLAB path:

1. At a MATLAB prompt, open the pathtool:

>>pathtool

2. Use the MATLAB pathtool to add the GenePatternServer and GenePatternFileSupport

directories, with subfolders, to the MATLAB search path.

Running a Program

This section explores a simple MATLAB program that runs a task, displays the resulting output, and loads it into a

MATLAB matrix for further analysis. The included code can be copied and pasted into your MATLAB client so that

you can try it out, modify it, and create your own solutions.

The first statements in the application initialize various settings, which you must do once in every application that

accesses GenePattern. You will need to customize the italicized GenePattern server URL and GenePattern user

name (typically, your e-mail address) with values appropriate for your GenePattern server.

% Create a GenePattern server proxy instance

gp = GenePatternServer('http://localhost:8080','[email protected]');

After initializing the required settings, the application runs the TransposeDataset task to transpose a dataset. This

example references the dataset using a publicly-accessible URL, but a filename would be equally valid. As shown

below, you can call the GenePattern methods directly or by calling the

runAnalysis method. When you call a

GenePattern method, such as

TransposeDataset, the GenePattern library invokes the task on the server,

passing all of the input parameters and input files. Control returns to your application when the task completes. (To

run a task asynchronously, invoke the method in a separate thread.)

% input dataset for transpose operation

params.output_file_name = 'transposed.out'

params.input_filename='http://www.broad.mit.edu/mpr/publications/projects/Leuk

emia/

ALL_vs_AML_train_set_38_sorted.res'

% transpose the dataset

transposeResult = gp.TransposeDataset(params)

% alternate call to transpose the dataset

transposeResult = runAnalysis(gp, 'TransposeDataset', params)

When the task completes, it returns a MATLAB structure that contains a list of filenames that are the output from the

task. In this example,

transposeResult is a structure with a list of filenames (of length 1, in this case). The

application displays the results in a file viewer window and also loads them into a matrix so that further manipulation

can be performed:

% display the transposed results

edit 'transposed.out.odf'

% now read the output into a matrix

% so we can do further manipulation in MATLAB

myData = loadGenePatternExpressionFile('transposed.out.odf')

You can combine GenePattern analyses with all of the rich functionality of MATLAB. For example, you can use

MATLAB's plotting methods to create graphic output, save modified matrices to files using save, or summarize and

report on the data using your own code. The basic idea to remember is that GenePattern tasks create result files and

those files are available to the MATLAB client for processing.

For a list of the GenePattern modules available on your server, run the

listMethods function on your

GenePatternServer object. To view the names of the input parameters for a module, use the

describeMethod function on your GenePatternServer object, passing it the module name.

% display the available GenePattern modules

listMethods(gp)

% now look at the parameters for the TransposeDataset module

describeMethod(gp, 'TransposeDataset')

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