Mercurial > repos > melpetera > corr_table

diff CorrTable/Corr.xml @ 1:29ec7e3afdd4 draft

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author melpetera
date Thu, 01 Aug 2019 11:30:58 -0400
parents b22c453e4cf4
children
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--- a/CorrTable/Corr.xml	Thu Oct 11 05:35:55 2018 -0400
+++ b/CorrTable/Corr.xml	Thu Aug 01 11:30:58 2019 -0400
@@ -1,4 +1,4 @@
-<tool id="corrtable" name="Between-table Correlation" version="0.0.0">
+<tool id="corrtable" name="Between-table Correlation" version="1.0.0">
 	<description>Correlation table between two tables and graphic representation </description>
 	  <requirements>
 			<requirement type="package" version="1.1_4">r-batch</requirement>
@@ -33,18 +33,23 @@
 		
 		reorder_var "$out_section.reorder_var"
 		
-		color_heatmap "${out_section.heatmap_cond.color_heatmap}"
-		#if str($out_section.heatmap_cond.color_heatmap) == 'yes' :
-			type_classes "${out_section.heatmap_cond.typeclass_cond.type_classes}"
-			#if str($out_section.heatmap_cond.typeclass_cond.type_classes) == 'regular' :
-				reg_class_value "${out_section.heatmap_cond.typeclass_cond.reg_class_value}"
-			#elif str($out_section.heatmap_cond.typeclass_cond.type_classes) == 'irregular' :
-				irreg_class_vect "${out_section.heatmap_cond.typeclass_cond.irreg_class_vect}"
-			#end if
+		plot_choice "$out_section.plot_cond.plot_choice"
+		#if str($out_section.plot_cond.plot_choice) == 'none' :
+			tabcorr_out "$tabcorr_out"
+		#else:
+			color_heatmap "${out_section.plot_cond.heatmap_cond.color_heatmap}"
+			#if str($out_section.plot_cond.heatmap_cond.color_heatmap) == 'yes' :
+				type_classes "${out_section.plot_cond.heatmap_cond.typeclass_cond.type_classes}"
+				#if str($out_section.plot_cond.heatmap_cond.typeclass_cond.type_classes) == 'regular' :
+					reg_class_value "${out_section.plot_cond.heatmap_cond.typeclass_cond.reg_class_value}"
+				#elif str($out_section.plot_cond.heatmap_cond.typeclass_cond.type_classes) == 'irregular' :
+					irreg_class_vect "${out_section.plot_cond.heatmap_cond.typeclass_cond.irreg_class_vect}"
+				#end if
+			#end if	
+			tabcorr_out "$tabcorr_out"
+			heatmap_out "$heatmap_out"
 		#end if	
-		
-		tabcorr_out "$tabcorr_out"
-		heatmap_out "$heatmap_out"
+
 		
 	</command>
 	
@@ -118,55 +123,142 @@
 			</conditional>		
 		</section>
 		
-		<section name="out_section" title="Graphical outputs" expanded="False">
+		<section name="out_section" title="Output options" expanded="False">
 			<param name="reorder_var" label="Reorder variables (using Hierarchical Cluster Analysis)" type="select" display="radio" help="">
 				<option value="no">No</option>
 				<option value="yes">Yes</option>
 			</param>
 		
-			<conditional name="heatmap_cond">
-				<param name="color_heatmap" label="Colored correlation table strategy" type="select" display="radio" help="Standard corresponds to a scale with a smooth gradient between three colors: red, white and green (continuous case). Customized creates classes for the correlation coefficients - the scale has discrete values.">
-					<option value="no">Standard</option>
-					<option value="yes">Customized</option>
+			<conditional name="plot_cond">
+				<param name="plot_choice" label="PDF output" type="select" help="To determine whether a colored correlation table is plotted.">
+					<option value="auto">Default</option>
+					<option value="forced">Always plot a colored table</option>
+					<option value="none">No colored table</option>
 				</param>		
 		
-				<when value="yes">
-					<conditional name="typeclass_cond">
-						<param name="type_classes" label="Choose the type of classes" type="select" display="radio" help="Regular means the classes have the same size. Irregular means it is possible to choose any intervals." >
-							<option value="regular">Regular classes</option>
-							<option value="irregular">Irregular classes</option>
-						</param>
+				<when value="auto">
+					<conditional name="heatmap_cond">
+					<param name="color_heatmap" label="Colored correlation table strategy" type="select" display="radio" help="Standard corresponds to a scale with a smooth gradient between three colors: red, white and green (continuous case). Customized creates classes for the correlation coefficients - the scale has discrete values.">
+						<option value="no">Standard</option>
+						<option value="yes">Customized</option>
+					</param>		
+			
+					<when value="yes">
+						<conditional name="typeclass_cond">
+							<param name="type_classes" label="Choose the type of classes" type="select" display="radio" help="Regular means the classes have the same size. Irregular means it is possible to choose any intervals." >
+								<option value="regular">Regular classes</option>
+								<option value="irregular">Irregular classes</option>
+							</param>
+								
+							<when value="regular">
+								<param name="reg_class_value" label="Class size" type="float" value="" help="Must be between 0 and 1" />
+							</when>
 							
-						<when value="regular">
-							<param name="reg_class_value" label="Class size" type="float" value="" help="Must be between 0 and 1" />
-						</when>
-						
-						<when value="irregular">
-							<param name="irreg_class_vect" label="Vector with values for classes" type="text" value="" help="The vector must be of the following form: (value1,value2,value3,..). The values must be between -1 and 1 not included. For example: (-0.8,-0.5,-0.4,0,0.4,0.5,0.8)." />
-						</when>
-					</conditional>	
+							<when value="irregular">
+								<param name="irreg_class_vect" label="Vector with values for classes" type="text" value="" help="The vector must be of the following form: (value1,value2,value3,..). The values must be between -1 and 1 not included. For example: (-0.8,-0.5,-0.4,0,0.4,0.5,0.8)." />
+							</when>
+						</conditional>	
+					</when>
+					
+					<when value ="no">	
+					</when>
+					
+					</conditional>
 				</when>
 				
-				<when value ="no">	
+				<when value ="forced">	
+					<conditional name="heatmap_cond">
+					<param name="color_heatmap" label="Colored correlation table strategy" type="select" display="radio" help="Standard corresponds to a scale with a smooth gradient between three colors: red, white and green (continuous case). Customized creates classes for the correlation coefficients - the scale has discrete values.">
+						<option value="no">Standard</option>
+						<option value="yes">Customized</option>
+					</param>		
+			
+					<when value="yes">
+						<conditional name="typeclass_cond">
+							<param name="type_classes" label="Choose the type of classes" type="select" display="radio" help="Regular means the classes have the same size. Irregular means it is possible to choose any intervals." >
+								<option value="regular">Regular classes</option>
+								<option value="irregular">Irregular classes</option>
+							</param>
+								
+							<when value="regular">
+								<param name="reg_class_value" label="Class size" type="float" value="" help="Must be between 0 and 1" />
+							</when>
+							
+							<when value="irregular">
+								<param name="irreg_class_vect" label="Vector with values for classes" type="text" value="" help="The vector must be of the following form: (value1,value2,value3,..). The values must be between -1 and 1 not included. For example: (-0.8,-0.5,-0.4,0,0.4,0.5,0.8)." />
+							</when>
+						</conditional>	
+					</when>
+					
+					<when value ="no">	
+					</when>
+					
+					</conditional>
 				</when>
+				
+				<when value ="none">	
+				</when>	
+
 	
 			</conditional>
+			
+			
 		</section>
 		
 	</inputs>	
 	
 	<outputs>
 		<data name="tabcorr_out" label="CorrTable" format="tabular" />
-		<data name="heatmap_out" label="CT_plot" format="pdf" />
+		<data name="heatmap_out" label="CT_plot" format="pdf" >
+			<filter>out_section['plot_cond']['plot_choice'] == 'auto' or out_section['plot_cond']['plot_choice'] == 'forced'</filter>
+		</data>
 	</outputs>
 	
+	
+	<tests>
+	  <test>
+        <param name="tab1_in" value="input1_tab1.tabular"/>
+        <param name="tab1_samples" value="column"/>
+        <param name="tab2_in" value="input1_tab2.txt"/>
+	    <param name="tab2_samples" value="row"/>
+	    <param name="corr_method" value="pearson"/>
+		<param name="test_corr" value="no"/>
+		<param name="filter" value="yes"/>
+		<param name="filters_choice" value="filters_0_thr"/>
+		<param name="threshold" value="0.3"/>
+		<param name="reorder_var" value="no"/>
+		<param name="plot_choice" value="auto"/>
+		<param name="color_heatmap" value="yes"/>
+		<param name="type_classes" value="irregular"/>
+		<param name="irreg_class_vect" value="(-0.8,-0.7,-0.5,-0.4,-0.3,-0.2,0,0.2,0.3,0.4,0.5,0.7,0.8)"/>
+        <output name="tabcorr_out" file="output1_CorrTable.tabular"/>
+	    <output name="heatmap_out" file="output1_CT_plot.pdf"/>
+	  </test>
+	  <test>
+        <param name="tab1_in" value="input2_dataMatrix_500.txt"/>
+        <param name="tab1_samples" value="column"/>
+        <param name="tab2_in" value="input2_dataMatrix_500.txt"/>
+	    <param name="tab2_samples" value="column"/>
+	    <param name="corr_method" value="pearson"/>
+		<param name="test_corr" value="no"/>
+		<param name="filter" value="yes"/>
+		<param name="filters_choice" value="filters_0_thr"/>
+		<param name="threshold" value="0.7"/>
+		<param name="reorder_var" value="no"/>
+		<param name="plot_choice" value="auto"/>
+		<param name="color_heatmap" value="no"/>
+        <output name="tabcorr_out" file="output2_CorrTable.tabular"/>
+	  </test>
+    </tests>
+	
+	
 	<help>
 	
 .. class:: infomark
 
 **Author:** 
 Ophelie Barbet for original code (PFEM - INRA) 
-Maintainer: Melanie Petera (PFEM - INRA - MetaboHUB)
+**Maintainer:** Melanie Petera (PFEM - INRA - MetaboHUB)
 
 ---------------------------------------------------
 
@@ -204,14 +296,12 @@
 Positions of samples in table 1 and table 2
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
         | Essential to correctly calculate the correlations.
-        |
 
 Method for calculating the correlation coefficients
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
         | - 'Pearson': Measures the intensity of the linear association between two continuous variables.
-		| - The 'Spearman' and 'Kendall' methods are explained in the R documentation of the 'cor' function as follows: " Kendall's tau or Spearman's rho statistic is used to estimate a rank-based measure of association. These are more robust and have been recommended if the data do not necessarily come from a bivariate normal distribution.".
-		|
-		
+        | - The 'Spearman' and 'Kendall' methods are explained in the R documentation of the 'cor' function as follows: " Kendall's tau or Spearman's rho statistic is used to estimate a rank-based measure of association. These are more robust and have been recommended if the data do not necessarily come from a bivariate normal distribution.".
+        
 Significance test for the correlation coefficients
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
         | This test is performed on each correlation coefficient, with the following hypotheses:
@@ -219,7 +309,6 @@
         |         H1: The correlation coefficient is significantly different from zero.
         |
         | Coefficients whose null hypothesis (H0) are not rejected are replaced by zeros in the correlation table.
-        |
 
 | **Method for multiple testing correction (only if significance test is 'Yes'):**
 | The 7 methods implemented in the 'p.adjust' R function are available and documented as follows:
@@ -233,7 +322,6 @@
 Filter the correlation table
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^	
         | Allows to reduce the correlation table size by keeping only variables considered relevant.
-        |
 
 | **Choose the filters to apply (only if filter is 'Yes'):**
 | 	- 'Only zero filter': Remove variables with all their correlation coefficients equal to zero.
@@ -241,25 +329,34 @@
 	
 | *Choose a threshold (only threshold filter is used):* A value between 0 and 1.
 |
+	
+Output options
+^^^^^^^^^^^^^^
+        | Allows to set some parameters for the correlation table output and the pdf file. 
 
-Reorder variables using Hierarchical Cluster Analysis (HCA)
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-        | Allows the most linked variables to be close in the correlation table.
-        | A HCA is performed on each input tables, with:
-        |    - 1 - correlation coefficient, as distance
-        |    - Ward as aggregation method.
-        |
+| **Reorder variables using Hierarchical Cluster Analysis (HCA):**
+| Allows the most linked variables to be close in the correlation table.
+| A HCA is performed on each input tables, with:
+|    - 1 - correlation coefficient, as distance
+|    - Ward as aggregation method.
+| 
 
-        
+| **PDF output:** To determine whether a colored correlation table is plotted.
+| 	- 'Default': generates a pdf file with a colored correlation table if the filtered table has no dimension above 1000 (number of lines or columns). 
+| 	- 'Always plot a colored table': used when you are not afraid of huge colored correlation table; to be used wisely.
+| 	- 'No colored table': the module will generate the correlation table in tabular format only (no pdf file). 
+|
+	
 Colored correlation table strategy
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-		| Allows to create a colored correlation table. Variables of table 1 and variables of table 2 are related using colored rectangles. 
-		| About the colors, the negative correlations are in red, more or less intense according to their position between -1 and 0, and the positive correlations in green, more or less intense according to their position between 0 and 1. The coefficients equal to 0 are in white.
-		| 	- 'Standard': the graphical representation has a scale with a smooth gradient between three colors: red, white and green.
-		| 	- 'Customized': the colored correlation table has coefficient classes. It is possible to create regular or irregular classes. The scale is discreet.
-		|
-		
+        | *Only available when* **PDF output** *is set to 'Default' or 'Always plot a colored table'.*
+        | Allows to create a colored correlation table. Variables of table 1 and variables of table 2 are related using colored rectangles. 
+        | About the colors, the negative correlations are in red, more or less intense according to their position between -1 and 0, and the positive correlations in green, more or less intense according to their position between 0 and 1. The coefficients equal to 0 are in white.
+        | 	- 'Standard': the graphical representation has a scale with a smooth gradient between three colors: red, white and green.
+        | 	- 'Customized': the colored correlation table has coefficient classes. It is possible to create regular or irregular classes. The scale is discreet.
+        
 | **Choose the type of classes (only if colored correlation table strategy is 'Customized'):**
+| 
 
 | 	- 'Regular': classes are all (or almost) the same size. 	
 | To realize these intervals, we start from 1 to go to 0 by taking a step of the size chosen by the user, and we make the symmetry for -1 towards 0. If the last step does not fall on the 0 value, we create a class between this last value and 0, smaller in size than the others. It is important to specify that 0 represents a class on its own, which is assigned the color white for the heatmap.	
@@ -267,7 +364,6 @@
 | *Size of classes (if regular classes):* A value between 0 and 1.
 
 | Example: if the size is 0.4, classes are [-1;-0.6], ]-0.6;-0.2], ]-0.2;0[, 0, ]0;0.2], ]0.2;0.6] and ]0.6;1].
-|
 
 | 	- 'Irregular': classes have variable lengths.
 | It is possible to do as many classes as you want, and of any size. There is not necessarily symmetry between -1 and 0, and 0 and 1. You can choose to have a white class with only 0, or an interval which contains the value 0.
@@ -276,7 +372,7 @@
 
 | Example: if the vector is (-0.8,-0.5,-0.4,0,0.4,0.5,0.8), the classes are [-1;-0.8], ]-0.8;-0.5], ]-0.5;-0.4], ]-0.4;0[, 0, ]0;0.4], ]0.4;0.5], ]0.5;0.8] and ]0.8;1].
 |
-
+	
 	
 ------------
 Output files
@@ -291,7 +387,7 @@
 Heatmap (colored correlation table)
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 	| Pdf output
-	| Colored representation of the correlation table. The coefficients are replaced by colors. A coefficient close to -1 is red, close to 0 white, and close to 1 in green.
+	| Colored representation of the correlation table. The coefficients are replaced by colors. A coefficient close to -1 is red, close to 0 white, and close to 1 green.
 	|