unifracweightedcommand.h

   1 #ifndef UNIFRACWEIGHTEDCOMMAND_H
   2 #define UNIFRACWEIGHTEDCOMMAND_H
   3
   4 /*
   5  *  unifracweightedcommand.h
   6  *  Mothur
   7  *
   8  *  Created by Sarah Westcott on 2/9/09.
   9  *  Copyright 2009 Schloss Lab UMASS Amherst. All rights reserved.
  10  *
  11  */
  12
  13 #include "command.hpp"
  14 #include "weighted.h"
  15 #include "treemap.h"
  16 #include "progress.hpp"
  17 #include "sharedutilities.h"
  18 #include "fileoutput.h"
  19 #include "readtree.h"
  20
  21 class UnifracWeightedCommand : public Command {
  22
  23         public:
  24                 UnifracWeightedCommand(string);
  25                 UnifracWeightedCommand();
  26                 ~UnifracWeightedCommand() {}
  27
  28                 vector<string> setParameters();
  29                 string getCommandName()                 { return "unifrac.weighted";            }
  30                 string getCommandCategory()             { return "Hypothesis Testing";          }
  31                 string getHelpString();
  32                 string getCitation() { return "Lozupone CA, Hamady M, Kelley ST, Knight R (2007). Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Appl Environ Microbiol 73: 1576-85. \nhttp://www.mothur.org/wiki/Unifrac.weighted"; }
  33                 string getDescription()         { return "generic tests that describes whether two or more communities have the same structure"; }
  34
  35                 int execute();
  36                 void help() { m->mothurOut(getHelpString()); }
  37
  38         private:
  39                 struct linePair {
  40                         int start;
  41                         int num;
  42                         linePair(int i, int j) : start(i), num(j) {}
  43                 };
  44                 vector<linePair> lines;
  45         TreeMap* tmap;
  46                 FileOutput* output;
  47                 vector<Tree*> T;           //user trees
  48                 vector<double> utreeScores;  //user tree unweighted scores
  49                 vector<double> WScoreSig;  //tree weighted score signifigance when compared to random trees - percentage of random trees with that score or lower.
  50                 vector<string> groupComb; // AB. AC, BC...
  51                 string sumFile, outputDir;
  52                 int iters, numGroups, numComp, counter;
  53                 vector< vector<double> > rScores;  //vector<weighted scores for random trees.> each group comb has an entry
  54                 vector< vector<double> > uScores;  //vector<weighted scores for user trees.> each group comb has an entry
  55                 vector< map<float, float> > rScoreFreq;  //map <weighted score, number of random trees with that score.> -vector entry for each combination.
  56                 vector< map<float, float> > rCumul;  //map <weighted score, cumulative percentage of number of random trees with that score or higher.> -vector entry for each c
  57                 map<float, float>  validScores;  //map contains scores from random
  58
  59                 bool abort, phylip, random, includeRoot, subsample, consensus;
  60                 string groups, itersString, outputForm, treefile, groupfile, namefile;
  61                 vector<string> Groups, outputNames; //holds groups to be used
  62                 int processors, numUniquesInName, subsampleSize, subsampleIters;
  63                 ofstream outSum;
  64                 map<string, string> nameMap;
  65
  66                 void printWSummaryFile();
  67                 void printWeightedFile();
  68                 void createPhylipFile();
  69                 //void removeValidScoresDuplicates();
  70                 int findIndex(float, int);
  71                 void calculateFreqsCumuls();
  72                 int createProcesses(Tree*,  vector< vector<string> >,  vector< vector<double> >&);
  73                 int driver(Tree*, vector< vector<string> >, int, int,  vector< vector<double> >&);
  74         int runRandomCalcs(Tree*, vector<double>);
  75         vector<Tree*> buildTrees(vector< vector<double> >&, int, TreeMap&);
  76         int getConsensusTrees(vector< vector<double> >&, int);
  77         int getAverageSTDMatrices(vector< vector<double> >&, int);
  78
  79 };
  80
  81
  82
  83 #endif