getmetacommunitycommand.h

   1 //
   2 //  getmetacommunitycommand.h
   3 //  Mothur
   4 //
   5 //  Created by SarahsWork on 4/9/13.
   6 //  Copyright (c) 2013 Schloss Lab. All rights reserved.
   7 //
   8
   9 #ifndef Mothur_getmetacommunitycommand_h
  10 #define Mothur_getmetacommunitycommand_h
  11
  12 #include "command.hpp"
  13 #include "inputdata.h"
  14 #include "qFinderDMM.h"
  15 #include "pam.h"
  16 #include "sharedsobscollectsummary.h"
  17 #include "sharedchao1.h"
  18 #include "sharedace.h"
  19 #include "sharednseqs.h"
  20 #include "sharedjabund.h"
  21 #include "sharedsorabund.h"
  22 #include "sharedjclass.h"
  23 #include "sharedsorclass.h"
  24 #include "sharedjest.h"
  25 #include "sharedsorest.h"
  26 #include "sharedthetayc.h"
  27 #include "sharedthetan.h"
  28 #include "sharedkstest.h"
  29 #include "whittaker.h"
  30 #include "sharedochiai.h"
  31 #include "sharedanderbergs.h"
  32 #include "sharedkulczynski.h"
  33 #include "sharedkulczynskicody.h"
  34 #include "sharedlennon.h"
  35 #include "sharedmorisitahorn.h"
  36 #include "sharedbraycurtis.h"
  37 #include "sharedjackknife.h"
  38 #include "whittaker.h"
  39 #include "odum.h"
  40 #include "canberra.h"
  41 #include "structeuclidean.h"
  42 #include "structchord.h"
  43 #include "hellinger.h"
  44 #include "manhattan.h"
  45 #include "structpearson.h"
  46 #include "soergel.h"
  47 #include "spearman.h"
  48 #include "structkulczynski.h"
  49 #include "structchi2.h"
  50 #include "speciesprofile.h"
  51 #include "hamming.h"
  52 #include "gower.h"
  53 #include "memchi2.h"
  54 #include "memchord.h"
  55 #include "memeuclidean.h"
  56 #include "mempearson.h"
  57 #include "sharedjsd.h"
  58
  59 /**************************************************************************************************/
  60
  61 class GetMetaCommunityCommand : public Command {
  62 public:
  63     GetMetaCommunityCommand(string);
  64     GetMetaCommunityCommand();
  65     ~GetMetaCommunityCommand(){}
  66
  67     vector<string> setParameters();
  68     string getCommandName()                     { return "get.communitytype";           }
  69     string getCommandCategory()         { return "OTU-Based Approaches";         }
  70
  71     string getOutputPattern(string);
  72
  73         string getHelpString();
  74     string getCitation() { return "Holmes I, Harris K, Quince C (2012) Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics. PLoS ONE 7(2): e30126. doi:10.1371/journal.pone.0030126 http://www.mothur.org/wiki/get.communitytype"; }
  75     string getDescription()             { return "Assigns samples to bins using a Dirichlet multinomial mixture model"; }
  76
  77     int execute();
  78     void help() { m->mothurOut(getHelpString()); }
  79
  80 private:
  81     struct linePair {
  82                 unsigned long long start;
  83                 unsigned long long end;
  84                 linePair(unsigned long long i, unsigned long long j) : start(i), end(j) {}
  85         };
  86     bool abort, allLines, subsample;
  87     string outputDir;
  88     vector<string> outputNames;
  89     string sharedfile, method, calc;
  90     int minpartitions, maxpartitions, optimizegap, processors, iters, subsampleSize;
  91     vector<string> Groups, Estimators;
  92     set<string> labels;
  93
  94     vector<vector<double> > generateDistanceMatrix(vector<SharedRAbundVector*>& lookup);
  95     int driver(vector<SharedRAbundVector*> thisLookup, vector< vector<seqDist> >& calcDists, Calculator*);
  96     int processDriver(vector<SharedRAbundVector*>&, vector<int>&, string, vector<string>, vector<string>, vector<string>, int);
  97     int createProcesses(vector<SharedRAbundVector*>&);
  98     vector<double> generateDesignFile(int, map<string,string>);
  99     int generateSummaryFile(int, map<string,string>, vector<double>);
 100
 101 };
 102
 103 /**************************************************************************************************/
 104 struct summaryData {
 105
 106     string name;
 107     double refMean, difference;
 108     vector<double> partMean, partLCI, partUCI;
 109
 110 };
 111
 112 #endif