Workflow and Statistical Analysis catalogs

An example: PCA

Overview of the interaction mechanism of the different file types

PCA.def

This definition file serves to automatically build the GUI of input masks of the analysis parameters with some default values, and also the the header of R scripts taken into account the initialization of parameters with the values given by the user.

GUI of input mask of the analysis parameters (automatically generated)

Header of the R code (automatically generated)

PCA.R - R code written by the provider

The R script written by the provider. It should not include the initialisation part of the parameters, given that the header of each script, automatically generated, takes into account this part. See above.

…

PCA.xml

This documentation file describes the analysis parameters within the input mask.

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE analysis>
<analysis name="PCA">
	<description>
Principal component analysis (PCA) is a mathematical procedure _NL_
that uses an orthogonal transformation to convert a set of observations _NL_
of possibly correlated variables into a set of values of linearly_NL_
uncorrelated variables called principal components. 
See [PCA|http://en.wikipedia.org/wiki/Principal_component_analysis]
        </description>
	<helptable>
		<setting>
			<field>Launch</field>
			<desc>
                              Field indicating whether you want to execute this 
                              analysis in the workflow (checked) or not (unchecked).
                         </desc>
			<example></example>
		</setting>
		<setting>
			<field>Scale</field>
			<desc>
                              Indicates whether the variables should be scaled to have unit variance 
                              before the analysis takes place.
                        </desc>
			<example>No by default (done in a previous step)</example>
		</setting>
		<setting>
			<field> Labels on Score graphs:</field>
			<desc>
                              Indicates whether the samples labels should be put in the Score plot.
                        </desc>
			<example>Yes (by default)</example>
		</setting>
		<setting>
			<field>Samples within ellipses</field>
			<desc>
                              Indicates whether ellipses should be drawn in the Scores plot around 
                              samples from the same factorial group.
                        </desc>
			<example>No (by default)</example>
		</setting>
	</helptable>
</analysis>