else {
//valid paramters for this command
- string Array[] = {"groups","iters"};
+ string Array[] = {"groups","iters","distance","random"};
vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
OptionParser parser(option);
itersString = validParameter.validFile(parameters, "iters", false); if (itersString == "not found") { itersString = "1000"; }
convert(itersString, iters);
+
+ string temp = validParameter.validFile(parameters, "distance", false); if (temp == "not found") { temp = "false"; }
+ phylip = isTrue(temp);
+ temp = validParameter.validFile(parameters, "random", false); if (temp == "not found") { temp = "true"; }
+ random = isTrue(temp);
+
+ if (!random) { iters = 0; } //turn off random calcs
+
if (abort == false) {
T = globaldata->gTree;
void UnifracWeightedCommand::help(){
try {
mothurOut("The unifrac.weighted command can only be executed after a successful read.tree command.\n");
- mothurOut("The unifrac.weighted command parameters are groups and iters. No parameters are required.\n");
+ mothurOut("The unifrac.weighted command parameters are groups, iters, distance and random. No parameters are required.\n");
mothurOut("The groups parameter allows you to specify which of the groups in your groupfile you would like analyzed. You must enter at least 2 valid groups.\n");
mothurOut("The group names are separated by dashes. The iters parameter allows you to specify how many random trees you would like compared to your tree.\n");
+ mothurOut("The distance parameter allows you to create a distance file from the results. The default is false.\n");
+ mothurOut("The random parameter allows you to shut off the comparison to random trees. The default is true, meaning compare your trees with randomly generated trees.\n");
mothurOut("The unifrac.weighted command should be in the following format: unifrac.weighted(groups=yourGroups, iters=yourIters).\n");
mothurOut("Example unifrac.weighted(groups=A-B-C, iters=500).\n");
mothurOut("The default value for groups is all the groups in your groupfile, and iters is 1000.\n");
if (abort == true) { return 0; }
Progress* reading;
- reading = new Progress("Comparing to random:", iters);
+ if (random) { reading = new Progress("Comparing to random:", iters); }
//get weighted for users tree
userData.resize(numComp,0); //data[0] = weightedscore AB, data[1] = weightedscore AC...
rScores.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
uScores.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
- output = new ColumnFile(globaldata->getTreeFile() + toString(i+1) + ".weighted", itersString);
+ if (random) { output = new ColumnFile(globaldata->getTreeFile() + toString(i+1) + ".weighted", itersString); }
userData = weighted->getValues(T[i]); //userData[0] = weightedscore
//removeValidScoresDuplicates();
//find the signifigance of the score for summary file
- for (int f = 0; f < numComp; f++) {
- //sort random scores
- sort(rScores[f].begin(), rScores[f].end());
+ if (random) {
+ for (int f = 0; f < numComp; f++) {
+ //sort random scores
+ sort(rScores[f].begin(), rScores[f].end());
+
+ //the index of the score higher than yours is returned
+ //so if you have 1000 random trees the index returned is 100
+ //then there are 900 trees with a score greater then you.
+ //giving you a signifigance of 0.900
+ int index = findIndex(userData[f], f); if (index == -1) { mothurOut("error in UnifracWeightedCommand"); mothurOutEndLine(); exit(1); } //error code
+
+ //the signifigance is the number of trees with the users score or higher
+ WScoreSig.push_back((iters-index)/(float)iters);
+ }
- //the index of the score higher than yours is returned
- //so if you have 1000 random trees the index returned is 100
- //then there are 900 trees with a score greater then you.
- //giving you a signifigance of 0.900
- int index = findIndex(userData[f], f); if (index == -1) { mothurOut("error in UnifracWeightedCommand"); mothurOutEndLine(); exit(1); } //error code
-
- //the signifigance is the number of trees with the users score or higher
- WScoreSig.push_back((iters-index)/(float)iters);
+ //out << "Tree# " << i << endl;
+ calculateFreqsCumuls();
+ printWeightedFile();
+
+ delete output;
}
- //out << "Tree# " << i << endl;
- calculateFreqsCumuls();
- printWeightedFile();
-
- delete output;
-
//clear data
rScores.clear();
uScores.clear();
}
//finish progress bar
- reading->finish();
- delete reading;
+ if (random) { reading->finish(); delete reading; }
printWSummaryFile();
+ if (phylip) { createPhylipFile(); }
+
//clear out users groups
globaldata->Groups.clear();
int count = 0;
for (int i = 0; i < T.size(); i++) {
for (int j = 0; j < numComp; j++) {
- if (WScoreSig[count] > (1/(float)iters)) {
- outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
- cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
- mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t" + toString(WScoreSig[count])); mothurOutEndLine();
+ if (random) {
+ if (WScoreSig[count] > (1/(float)iters)) {
+ outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
+ cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
+ mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t" + toString(WScoreSig[count])); mothurOutEndLine();
+ }else{
+ outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
+ cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
+ mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t<" + toString((1/float(iters)))); mothurOutEndLine();
+ }
}else{
- outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
- cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
- mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t<" + toString((1/float(iters)))); mothurOutEndLine();
+ outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << "0.00" << endl;
+ cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << "0.00" << endl;
+ mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t0.00"); mothurOutEndLine();
}
count++;
}
exit(1);
}
}
+/***********************************************************/
+void UnifracWeightedCommand::createPhylipFile() {
+ try {
+ int count = 0;
+ //for each tree
+ for (int i = 0; i < T.size(); i++) {
+
+ string phylipFileName = globaldata->getTreeFile() + toString(i+1) + ".weighted.dist";
+ ofstream out;
+ openOutputFile(phylipFileName, out);
+
+ //output numSeqs
+ out << globaldata->Groups.size() << endl;
+
+ //make matrix with scores in it
+ vector< vector<float> > dists; dists.resize(globaldata->Groups.size());
+ for (int i = 0; i < globaldata->Groups.size(); i++) {
+ dists[i].resize(globaldata->Groups.size(), 0.0);
+ }
+
+ //flip it so you can print it
+ for (int r=0; r<globaldata->Groups.size(); r++) {
+ for (int l = r+1; l < globaldata->Groups.size(); l++) {
+ dists[r][l] = (1.0 - utreeScores[count]);
+ dists[l][r] = (1.0 - utreeScores[count]);
+ count++;
+ }
+ }
+ //output to file
+ for (int r=0; r<globaldata->Groups.size(); r++) {
+ //output name
+ out << globaldata->Groups[r] << '\t';
+
+ //output distances
+ for (int l = 0; l < r; l++) { out << dists[r][l] << '\t'; }
+ out << endl;
+ }
+ out.close();
+ }
+ }
+ catch(exception& e) {
+ errorOut(e, "UnifracWeightedCommand", "createPhylipFile");
+ exit(1);
+ }
+}
/***********************************************************/
int UnifracWeightedCommand::findIndex(float score, int index) {
try{
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