X-Git-Url: https://git.donarmstrong.com/?p=mothur.git;a=blobdiff_plain;f=lefsecommand.h;h=c9c4092e99f6bb402145f2e3432753ce642c7c6e;hp=095ad48da125fbfe83f30aaff41eb62ec18c610f;hb=b25ede2ad307ae76f8a610443e0ec3ec69621ce7;hpb=b8ff3bca0560a53832723f4621fcddef7ec4e499

diff --git a/lefsecommand.h b/lefsecommand.h
index 095ad48..c9c4092 100644
--- a/lefsecommand.h
+++ b/lefsecommand.h
@@ -12,7 +12,7 @@
 #include "command.hpp"
 
 /* 
- Columns = groups, rows are OTUs, class = design??
+ Columns = groups, rows are OTUs, class = design
  
  From http://huttenhower.sph.harvard.edu/galaxy/root?tool_id=lefse_upload
  Input data consist of a collection of m samples (columns) each made up of n numerical features (rows, typically normalized per-sample, red representing high values and green low). These samples are labeled with a class (taking two or more possible values) that represents the main biological hypothesis under investigation; they may also have one or more subclass labels reflecting within-class groupings.
@@ -22,4 +22,47 @@
  Step 3: the resulting subset of vectors is used to build a Linear Discriminant Analysis model from which the relative difference among classes is used to rank the features. The final output thus consists of a list of features that are discriminative with respect to the classes, consistent with the subclass grouping within classes, and ranked according to the effect size with which they differentiate classes.
 */
 
+
+#include "command.hpp"
+#include "inputdata.h"
+#include "designmap.h"
+
+/**************************************************************************************************/
+
+class LefseCommand : public Command {
+public:
+    LefseCommand(string);
+    LefseCommand();
+    ~LefseCommand(){}
+    
+    vector<string> setParameters();
+    string getCommandName()			{ return "lefse";			}
+    string getCommandCategory()		{ return "OTU-Based Approaches";		}
+    
+    string getOutputPattern(string);
+	string getHelpString();
+    string getCitation() { return "http://www.mothur.org/wiki/Lefse"; }
+    string getDescription()		{ return "brief description"; }
+    
+    int execute();
+    void help() { m->mothurOut(getHelpString()); }
+    
+private:
+    bool abort, allLines;
+    string outputDir, sharedfile, designfile, mclass, subclass, classes;
+    vector<string> outputNames;
+    set<string> labels;
+    float anovaAlpha, wilcoxonAlpha;
+    
+    int process(vector<SharedRAbundVector*>&, DesignMap&);
+    vector<int> runKruskalWallis(vector<SharedRAbundVector*>&, DesignMap&);
+    vector<int> runWilcoxon(vector<SharedRAbundVector*>&, DesignMap&, vector<int>);
+
+};
+
+/**************************************************************************************************/
+
+
+
+
 #endif /* defined(__Mothur__lefsecommand__) */