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//
// lefsecommand.h
// Mothur
//
// Created by SarahsWork on 6/12/13.
// Copyright (c) 2013 Schloss Lab. All rights reserved.
//
#ifndef __Mothur__lefsecommand__
#define __Mothur__lefsecommand__
#include "command.hpp"
/*
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.
Step 1: the Kruskall-Wallis test analyzes all features, testing whether the values in different classes are differentially distributed. Features violating the null hypothesis are further analyzed in Step 2.
Step 2: the pairwise Wilcoxon test checks whether all pairwise comparisons between subclasses within different classes significantly agree with the class level trend.
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"
#include "sharedclrvectors.hpp"
/**************************************************************************************************/
class LefseCommand : public Command {
public:
LefseCommand(string);
~LefseCommand(){}
vector<string> setParameters();
string getCommandName() { return "lefse"; }
string getCommandCategory() { return "OTU-Based Approaches"; }
string getOutputPattern(string);
string getHelpString();
string getCitation() { return "Segata, N., J. Izard, L. Waldron, D. Gevers, L. Miropolsky, W. S. Garrett, and C. Huttenhower. 2011. Metagenomic biomarker discovery and explanation. Genome Biol 12:R60, http://www.mothur.org/wiki/Lefse"; }
string getDescription() { return "brief description"; }
int execute();
void help() { m->mothurOut(getHelpString()); }
private:
bool abort, allLines, wilc, wilcsamename, curv, subject, normMillion, pairwise, runAll;
string sharedfile, designfile, mclass, subclass, rankTec, multiClassStrat, sets, inputfile, clrfile, format;
vector<string> outputNames, Sets;
set<string> labels;
double anovaAlpha, wilcoxonAlpha, fBoots, ldaThreshold;
int nlogs, iters, strict, minC;
int process(SharedRAbundFloatVectors*&, SharedCLRVectors*&, DesignMap&, string combo);
int normalize(SharedRAbundFloatVectors*&, SharedCLRVectors*&);
map<int, double> runKruskalWallis(SharedRAbundFloatVectors*&, SharedCLRVectors*&, DesignMap&);
map<int, double> runWilcoxon(SharedRAbundFloatVectors*&, SharedCLRVectors*&, map<int, double>, map<string, set<string> >& class2SubClasses, map<string, vector<int> >& subClass2GroupIndex, map<string, string>);
map<int, double> testLDA(SharedRAbundFloatVectors*&, SharedCLRVectors*&, map<int, double>, map<string, vector<int> >& class2GroupIndex, map<string, vector<int> >&);
vector< vector<double> > getMeans(SharedRAbundFloatVectors*& lookup, SharedCLRVectors*& clr, map<string, vector<int> >& class2GroupIndex);
bool contastWithinClassesOrFewPerClass(vector< vector<double> >&, vector<int> rands, int minCl, map<string, vector<int> > class2GroupIndex, map<int, string> indexToClass);
vector< vector<double> > lda(vector< vector<double> >& adjustedLookup, vector<int> rand_s, map<int, string>& indexToClass, vector<string>);
bool testOTUWilcoxon(map<string, set<string> >& class2SubClasses, vector<float> abunds, map<string, vector<int> >& subClass2GroupIndex, map<string, string>);
void printResults(vector< vector<double> >, map<int, double>, map<int, double>, string, vector<string>, vector<string>, string);
void printResultsAll(vector< vector<double> >, map<int, double>, map<int, double>, string, vector<string>, vector<string>, string);
//for testing
bool printToCoutForRTesting(vector< vector<double> >& adjustedLookup, vector<int> rand_s, map<string, vector<int> >& class2GroupIndex, map<int, double> bins, map<string, vector<int> >&, vector<string>, vector<string>);
int makeShared(int);
void runPairwiseAnalysis(DesignMap&);
};
/**************************************************************************************************/
#endif /* defined(__Mothur__lefsecommand__) */
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