1 | /* |
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2 | * Analyser.cpp |
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3 | * |
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4 | * Responsible for interacting with the Cma code and Arb. |
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5 | * |
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6 | * Created on: Feb 15, 2010 |
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7 | * Author: breno |
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8 | * |
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9 | * Institute of Microbiology (Technical University Munich) |
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10 | * http://www.arb-home.de/ |
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11 | */ |
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12 | |
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13 | #include "Analyser.h" |
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14 | |
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15 | #include <ctime> |
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16 | #include <iostream> |
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17 | #include <iterator> |
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18 | |
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19 | /** |
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20 | * Constructor |
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21 | */ |
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22 | Analyser::Analyser(GBDATA *gb_main) : |
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23 | loader(NULp), |
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24 | cma(NULp) |
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25 | { |
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26 | |
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27 | //Definition of the alphabet |
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28 | vector<string> alphabet(0); |
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29 | alphabet.push_back("A"); |
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30 | alphabet.push_back("C"); |
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31 | alphabet.push_back("G"); |
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32 | alphabet.push_back("T"); |
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33 | |
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34 | loader = new AlignedSequenceLoader(gb_main); |
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35 | if (!loader->has_error()) { |
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36 | VecVecType *seqs = loader->getSequences(); |
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37 | cma = new Cma(alphabet, seqs->size()); |
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38 | } |
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39 | } |
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40 | |
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41 | /** |
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42 | * Destructor. |
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43 | */ |
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44 | Analyser::~Analyser() { |
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45 | delete loader; |
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46 | delete cma; |
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47 | } |
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48 | |
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49 | /** |
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50 | * Getter for the Cma object. |
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51 | * |
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52 | * @return the Cma object. |
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53 | */ |
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54 | Cma* Analyser::getCma() { |
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55 | arb_assert(!has_error()); |
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56 | return cma; |
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57 | } |
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58 | |
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59 | /** |
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60 | * Returns the AlignedSequenceLoader object. |
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61 | * |
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62 | * @return the AlignedSequenceLoader object. |
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63 | */ |
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64 | AlignedSequenceLoader* Analyser::getLoader() { |
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65 | return loader; |
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66 | } |
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67 | |
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68 | /** |
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69 | * Saves the clusters to the DB as SAI. |
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70 | * |
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71 | * @param clusters: the cluster indices. |
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72 | * @param threshold: the clustering threshold used. |
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73 | * |
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74 | * @return an GB_ERROR if some DB transaction fails. |
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75 | */ |
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76 | GB_ERROR Analyser::saveSAI(GBDATA *gb_main, vector<size_t> clusters, double threshold) { |
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77 | GB_ERROR error = GB_push_transaction(gb_main); |
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78 | |
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79 | if (!error) { |
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80 | char *al_name = GBT_get_default_alignment(gb_main); |
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81 | if (!al_name) { |
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82 | error = GB_await_error(); |
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83 | } |
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84 | else { |
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85 | vector<char> clusts = normalizeClusters(clusters); |
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86 | // build result string |
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87 | stringstream ss; |
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88 | copy(clusts.begin(), clusts.end(), ostream_iterator<char> (ss, "")); |
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89 | string result = ss.str(); |
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90 | |
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91 | //save |
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92 | GBDATA *gb_sai = GBT_find_or_create_SAI(gb_main, getSAIname()); |
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93 | GBDATA *gb_data = GBT_add_data(gb_sai, al_name, "data", GB_STRING); |
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94 | error = GB_write_string(gb_data, result.c_str()); |
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95 | |
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96 | if (!error) { |
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97 | GBDATA *gb_options = GBT_add_data(gb_sai, al_name, "_TYPE", GB_STRING); |
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98 | stringstream options; |
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99 | options << "CMA_CLUSTERING: [threshold: " << threshold << "]"; |
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100 | |
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101 | error = GB_write_string(gb_options, options.str().c_str()); |
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102 | } |
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103 | free(al_name); |
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104 | } |
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105 | } |
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106 | error = GB_end_transaction(gb_main, error); |
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107 | |
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108 | return error; |
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109 | } |
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110 | |
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111 | /** |
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112 | * Gives clusters a reasonable name. The clustering algorithm may return |
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113 | * clusters with indices 123 even though there are only 50 clusters. |
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114 | * Here we normalise the cluster names, in this example we would have |
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115 | * only clusters from 0..50 as result. |
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116 | * |
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117 | * @param clusters: the result of the clustering algorithm. |
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118 | * |
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119 | * @return the new cluster names (note that the cluster index is a char |
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120 | * because we have to be able to show it in the SAI, where we |
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121 | * are allowed to use only one character for each position). |
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122 | */ |
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123 | vector<char> Analyser::normalizeClusters(vector<size_t> clusters) { |
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124 | |
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125 | vector<char> result; |
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126 | map<unsigned int, char> rename_map; |
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127 | rename_map[0] = '-'; |
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128 | char classes = '0'; |
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129 | |
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130 | for (vector<size_t>::iterator it = clusters.begin(); it != clusters.end(); ++it) { |
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131 | if (rename_map.find(*it) == rename_map.end()) { |
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132 | rename_map[*it] = classes++; |
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133 | } |
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134 | result.push_back(rename_map[*it]); |
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135 | } |
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136 | return result; |
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137 | |
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138 | } |
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139 | |
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140 | //-------------------------------- |
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141 | |
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142 | GB_ERROR run_rnacma(GBDATA *gb_main, bool interactive, double threshold) { |
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143 | /*! interactive main loop of RNACMA. |
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144 | * @param gb_main the database. |
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145 | * @param interactive normally true. set to false for (non-interactive) unittesting. |
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146 | * @param threshold only used if !interactive (i.e. for unittesting) |
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147 | */ |
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148 | |
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149 | GB_ERROR error = NULp; |
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150 | try { |
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151 | Analyser a(gb_main); |
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152 | error = a.get_error(); |
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153 | |
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154 | if (!error) { |
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155 | Cma *cma = a.getCma(); |
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156 | |
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157 | cma->computeMutualInformationP(*(a.getLoader()->getSequences())); |
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158 | |
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159 | list<MITuple> mituple = cma->compute_mituples(cma->getMIp()); |
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160 | |
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161 | cout << endl |
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162 | << "The highest MI value was: " << mituple.begin()->MI |
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163 | << " at position (" << mituple.begin()->pos1 << ", " |
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164 | << mituple.begin()->pos2 << ")." << endl |
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165 | << "(Note: pairs with MI-values down to the threshold will be joined in one cluster)" << endl; |
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166 | |
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167 | while (true) { |
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168 | if (interactive) { |
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169 | cout << endl |
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170 | << "Press Ctrl-d to quit or" << endl |
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171 | << "choose a threshold value for the clustering process: "; |
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172 | |
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173 | |
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174 | string input; |
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175 | cin >> input; |
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176 | |
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177 | if (input.empty()) { |
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178 | cout << endl << "quit" << endl; |
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179 | break; |
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180 | } |
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181 | |
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182 | threshold = strtod(input.c_str(), NULp); |
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183 | } |
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184 | cout << "Building clusters with threshold = " << threshold << endl; |
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185 | |
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186 | VectorXi cl = cma->computeClusters(mituple, size_t(cma->getMIp().cols()), threshold); |
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187 | vector<size_t> *clusters = new vector<size_t> (0, 0); |
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188 | AlignedSequenceLoader *l = a.getLoader(); |
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189 | size_t i = 0; |
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190 | size_t j = 0; |
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191 | for (vector<size_t>::const_iterator it = l->getPositionMap().begin(); it != l->getPositionMap().end(); ++it) { |
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192 | while (i < *it) { |
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193 | clusters->push_back(0); |
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194 | i++; |
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195 | } |
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196 | clusters->push_back(cl[j]); |
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197 | j++; |
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198 | i++; |
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199 | } |
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200 | |
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201 | GB_ERROR e = a.saveSAI(gb_main, *clusters, threshold); |
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202 | delete clusters; |
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203 | |
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204 | if (e) { |
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205 | cout << "Error while saving SAI: " << e << endl; |
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206 | throw e; |
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207 | } |
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208 | else { |
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209 | cout << "Saved results to SAI '" << Analyser::getSAIname() << "'" << endl |
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210 | << "(To analyse the results, open the editor and visualise the clusters using the SAI annotations)" << endl; |
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211 | } |
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212 | |
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213 | if (!interactive) break; |
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214 | } |
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215 | } |
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216 | } |
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217 | catch (const char *err) { |
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218 | error = GBS_global_string("caught exception: %s", err); |
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219 | } |
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220 | return error; |
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221 | } |
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222 | |
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223 | int ARB_main(int /*argc*/, char */*argv*/[]) { |
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224 | cout |
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225 | << "arb_rnacma -- correlated mutation analysis" << endl |
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226 | << " computes clusters of correlated positions" << endl |
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227 | << "(C) 2010 The ARB-project" << endl |
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228 | << "Written 2009/2010 by Breno Faria" << endl |
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229 | << endl |
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230 | << "arb_rnacma uses the eigen C++ library (http://eigen.tuxfamily.org/)" << endl |
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231 | << "eigen is copyrighted by LGPL3" << endl |
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232 | << endl; |
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233 | |
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234 | int exitcode = EXIT_SUCCESS; |
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235 | { |
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236 | GB_ERROR error = NULp; |
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237 | { |
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238 | GB_shell shell; |
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239 | GBDATA *gb_main = GB_open(":", "rwt"); |
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240 | |
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241 | if (!gb_main) { |
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242 | error = GB_await_error(); |
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243 | } |
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244 | else { |
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245 | error = run_rnacma(gb_main, true, 0.0); |
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246 | } |
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247 | GB_close(gb_main); |
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248 | } |
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249 | |
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250 | if (error) { |
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251 | cout << endl << "Error in arb_rnacma: " << error << ". terminating." << endl; |
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252 | exitcode = EXIT_FAILURE; |
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253 | } |
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254 | } |
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255 | |
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256 | return exitcode; |
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257 | } |
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258 | |
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259 | // -------------------------------------------------------------------------------- |
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260 | |
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261 | #ifdef UNIT_TESTS |
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262 | #ifndef TEST_UNIT_H |
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263 | #include <test_unit.h> |
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264 | #endif |
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265 | |
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266 | void TEST_RNACMA() { |
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267 | GB_shell shell; |
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268 | { |
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269 | const char *db = "TEST_nuc_short.arb"; // ../UNIT_TESTER/run/TEST_nuc_short.arb |
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270 | const char *aliname = "ali_16s"; |
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271 | const char *sainame = "cma_clusters"; |
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272 | |
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273 | GBDATA *gb_main; |
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274 | TEST_EXPECT_RESULT__NOERROREXPORTED(gb_main = GB_open(db, "rw")); |
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275 | |
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276 | const int NO_OF_MARKED = 8; |
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277 | TEST_EXPECT_EQUAL(GBT_count_marked_species(gb_main), NO_OF_MARKED); |
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278 | |
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279 | { |
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280 | GB_transaction ta(gb_main); |
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281 | TEST_EXPECT_NORESULT__NOERROREXPORTED(GBT_find_SAI(gb_main, sainame)); // expect SAI to be missing |
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282 | } |
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283 | |
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284 | { |
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285 | GB_transaction ta(gb_main); |
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286 | |
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287 | struct { |
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288 | double threshold; |
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289 | const char *expected_clusters_data; |
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290 | } data[] = { |
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291 | { 0.5, "--------------------------0-----10-----0---------------------23--041---000--5-55-----000060----------0600005---55575-7----5000140--3----0--0--------------2-6------0--0000--000--------0000------0-00----------0------0-00000-0-" }, |
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292 | { 0.666, "--------------------------0------1-----1----------------------2--13----456--7-88-----9::0;------------;004:8---888<7-<----8494-3---2----5--5----------------;----------16---199---------01---------------------9------:--::99---" }, |
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293 | { 0.833, "----------------------------------------------------------------------------0--1-----2-------------------------111-0---------------------------------------------------------3---------------------------------3------------2---" }, |
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294 | { 1.0, "-------------------------------------------------------------------------------0--------------------------------00-----------------------------------------------------------1---------------------------------1----------------" }, |
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295 | { 1.5, "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------" }, |
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296 | |
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297 | // output for testdata: "The highest MI value was: 1.48 at position (77, 106)." |
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298 | { -1.0, NULp } |
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299 | }; |
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300 | |
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301 | TEST_EXPECT_NO_ERROR(run_rnacma(gb_main, false, data[0].threshold)); |
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302 | |
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303 | GBDATA *gb_sai = GBT_find_SAI(gb_main, sainame); |
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304 | TEST_REJECT_NULL(gb_sai); |
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305 | |
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306 | // test sai content: |
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307 | GBDATA *gb_sai_data = GBT_find_sequence(gb_sai, aliname); |
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308 | TEST_REJECT_NULL(gb_sai_data); |
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309 | |
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310 | int idx = 0; |
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311 | while (1) { |
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312 | TEST_ANNOTATE(GBS_global_string("idx=%i", idx)); |
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313 | const char *sai_data = GB_read_char_pntr(gb_sai_data); |
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314 | TEST_EXPECT_EQUAL(sai_data, data[idx].expected_clusters_data); |
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315 | |
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316 | ++idx; |
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317 | if (!data[idx].expected_clusters_data) break; // continue as long there are results to test |
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318 | |
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319 | TEST_EXPECT_NO_ERROR(run_rnacma(gb_main, false, data[idx].threshold)); |
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320 | } |
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321 | } |
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322 | |
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323 | const int SOME_THRESHOLD = 0.5; |
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324 | |
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325 | // fail on invalid default alignment: |
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326 | { |
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327 | GB_transaction ta(gb_main); |
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328 | TEST_EXPECT_NO_ERROR(GBT_set_default_alignment(gb_main, "ali_fantasy")); |
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329 | TEST_EXPECT_ERROR_CONTAINS(run_rnacma(gb_main, false, SOME_THRESHOLD), "alignment 'ali_fantasy' not found"); |
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330 | ta.close("abort"); // undo change of default alignment |
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331 | } |
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332 | |
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333 | // want failure if a marked sequence lacks data: |
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334 | for (int fail = 1; fail<=2; ++fail) { |
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335 | TEST_ANNOTATE(GBS_global_string("fail=%i", fail)); |
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336 | |
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337 | GBDATA *gb_species; |
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338 | { |
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339 | GB_transaction ta(gb_main); |
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340 | |
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341 | gb_species = GBT_first_marked_species(gb_main); |
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342 | GBDATA *gb_data = GBT_find_sequence(gb_species, aliname); |
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343 | |
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344 | switch (fail) { |
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345 | case 1: { |
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346 | GB_topSecurityLevel permit(gb_main); |
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347 | TEST_EXPECT_NO_ERROR(GB_delete(gb_data)); |
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348 | break; |
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349 | } |
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350 | case 2: { |
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351 | GBDATA *gb_ali = GB_get_father(gb_data); |
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352 | TEST_EXPECT_NO_ERROR(GB_delete(gb_ali)); |
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353 | break; |
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354 | } |
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355 | default: arb_assert(0); break; |
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356 | } |
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357 | |
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358 | TEST_EXPECT_ERROR_CONTAINS(run_rnacma(gb_main, false, SOME_THRESHOLD), "species 'LcbPont2' has no data in selected alignment 'ali_16s'"); |
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359 | |
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360 | ta.close("abort"); // undo changes |
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361 | } |
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362 | { |
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363 | // somehow the species flag is reset by the above (aborted) transaction. |
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364 | // @@@ could be a general database bug!? undo delete is known to be problematic (see #496) |
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365 | GB_transaction ta(gb_main); |
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366 | GB_write_flag(gb_species, 1); |
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367 | } |
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368 | } |
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369 | TEST_ANNOTATE(NULp); |
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370 | TEST_EXPECT_EQUAL(GBT_count_marked_species(gb_main), NO_OF_MARKED); |
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371 | |
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372 | // @@@ provoke some more errors? |
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373 | |
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374 | // test failure when no species marked: |
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375 | { |
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376 | GB_transaction ta(gb_main); |
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377 | GBT_mark_all(gb_main, 0); |
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378 | TEST_EXPECT_ERROR_CONTAINS(run_rnacma(gb_main, false, SOME_THRESHOLD), "caught exception: no (marked?) sequences"); |
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379 | ta.close("abort"); // undo changes |
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380 | } |
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381 | |
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382 | // Note that marks are correctly restored by aborting TA |
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383 | TEST_EXPECT_EQUAL(GBT_count_marked_species(gb_main), NO_OF_MARKED); |
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384 | |
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385 | GB_close(gb_main); |
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386 | } |
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387 | } |
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388 | |
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389 | #endif // UNIT_TESTS |
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390 | |
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391 | // -------------------------------------------------------------------------------- |
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