CommandParameter pclass("class", "String", "", "", "", "", "","",false,false); parameters.push_back(pclass);
CommandParameter psubclass("subclass", "String", "", "", "", "", "","",false,false); parameters.push_back(psubclass);
CommandParameter plabel("label", "String", "", "", "", "", "","",false,false); parameters.push_back(plabel);
- CommandParameter pclasses("classes", "String", "", "", "", "", "","",false,false); parameters.push_back(pclasses);
+ //CommandParameter pclasses("classes", "String", "", "", "", "", "","",false,false); parameters.push_back(pclasses);
CommandParameter palpha("aalpha", "Number", "", "0.05", "", "", "","",false,false); parameters.push_back(palpha);
CommandParameter pwalpha("walpha", "Number", "", "0.05", "", "", "","",false,false); parameters.push_back(pwalpha);
try {
string helpString = "";
helpString += "The lefse command allows you to ....\n";
- helpString += "The lefse command parameters are: shared, design, class, subclass, label, classes, walpha, aalpha, lda, wilc, iters, curv, fboots, strict, minc, multiclass and norm.\n";
+ helpString += "The lefse command parameters are: shared, design, class, subclass, label, walpha, aalpha, lda, wilc, iters, curv, fboots, strict, minc, multiclass and norm.\n";
helpString += "The class parameter is used to indicate the which category you would like used for the Kruskal Wallis analysis. If none is provided first category is used.\n";
helpString += "The subclass parameter is used to indicate the .....If none is provided, second category is used, or if only one category subclass is ignored. \n";
helpString += "The aalpha parameter is used to set the alpha value for the Krukal Wallis Anova test Default=0.05. \n";
helpString += "The wilc parameter is used to indicate whether to perform the Wilcoxon test. Default=T. \n";
helpString += "The iters parameter is used to set the number of bootstrap iteration for LDA. Default=30. \n";
//helpString += "The wilcsamename parameter is used to indicate whether perform the wilcoxon test only among the subclasses with the same name. Default=F. \n";
- helpString += "The curv parameter is used to set whether perform the wilcoxon test ing the Curtis's approach [BETA VERSION] Default=F. \n";
+ helpString += "The curv parameter is used to set whether perform the wilcoxon testing the Curtis's approach [BETA VERSION] Default=F. \n";
helpString += "The norm parameter is used to multiply relative abundances by 1000000. Recommended when very low values are present. Default=T. \n";
helpString += "The fboots parameter is used to set the subsampling fraction value for each bootstrap iteration. Default=0.67. \n";
helpString += "The strict parameter is used to set the multiple testing correction options. 0 no correction (more strict, default), 1 correction for independent comparisons, 2 correction for independent comparison. Options = 0,1,2. Default=0. \n";
helpString += "The minc parameter is used to minimum number of samples per subclass for performing wilcoxon test. Default=10. \n";
helpString += "The multiclass parameter is used to (for multiclass tasks) set whether the test is performed in a one-against-one ( onevone - more strict!) or in a one-against-all setting ( onevall - less strict). Default=onevall. \n";
- helpString += "The classes parameter is used to indicate the classes you would like to use. Classes should be inputted in the following format: classes=label<value1|value2|value3>-label<value1|value2>. For example to include groups from treatment with value early or late and age= young or old. class=treatment<Early|Late>-age<young|old>.\n";
+ //helpString += "The classes parameter is used to indicate the classes you would like to use. Classes should be inputted in the following format: classes=label<value1|value2|value3>-label<value1|value2>. For example to include groups from treatment with value early or late and age= young or old. class=treatment<Early|Late>-age<young|old>.\n";
helpString += "The label parameter is used to indicate which distances in the shared file you would like to use. labels are separated by dashes.\n";
helpString += "The lefse command should be in the following format: lefse(shared=final.an.shared, design=final.design, class=treatment, subclass=age).\n";
return helpString;
subclass = validParameter.validFile(parameters, "subclass", false);
if (subclass == "not found") { subclass = mclass; }
- classes = validParameter.validFile(parameters, "classes", false);
- if (classes == "not found") { classes = ""; }
-
string temp = validParameter.validFile(parameters, "aalpha", false);
if (temp == "not found") { temp = "0.05"; }
m->mothurConvert(temp, anovaAlpha);
int LefseCommand::execute(){
try {
+ srand(1982);
//for reading lefse formatted file and running in mothur for testing - pass number of rows used for design file
if (false) { makeShared(1); exit(1); }
if (abort == true) { if (calledHelp) { return 0; } return 2; }
DesignMap designMap(designfile);
- //if user set classes set groups=those classes
- if (classes != "") {
- map<string, vector<string> > thisClasses = m->parseClasses(classes);
- vector<string> groups = designMap.getNamesUnique(thisClasses);
- if (groups.size() != 0) { m->setGroups(groups); }
- else { m->mothurOut("[ERROR]: no groups meet your classes requirement, quitting.\n"); return 0; }
- }
//if user did not select class use first column
- if (mclass == "") { mclass = designMap.getDefaultClass(); m->mothurOut("\nYou did not provide a class, using " + mclass +".\n\n"); }
+ if (mclass == "") { mclass = designMap.getDefaultClass(); m->mothurOut("\nYou did not provide a class, using " + mclass +".\n\n"); if (subclass == "") { subclass = mclass; } }
InputData input(sharedfile, "sharedfile");
vector<SharedRAbundFloatVector*> lookup = input.getSharedRAbundFloatVectors();
m->mothurOut("Output File Names: "); m->mothurOutEndLine();
for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i]); m->mothurOutEndLine(); }
m->mothurOutEndLine();
+ srand(time(NULL));
return 0;
}
map<string, set<string> > class2SubClasses; //maps class name to vector of its subclasses
map<string, vector<int> > subClass2GroupIndex; //maps subclass name to vector of indexes in lookup from that subclass. old -> 1,2,3 means groups in location 1,2,3 of lookup are from old. Saves time below.
map<string, vector<int> > class2GroupIndex; //maps subclass name to vector of indexes in lookup from that class. old -> 1,2,3 means groups in location 1,2,3 of lookup are from old. Saves time below.
+ if (normMillion) { normalize(lookup); }
for (int j = 0; j < lookup.size(); j++) {
- if (normMillion) { normalize(lookup); }
string group = lookup[j]->getGroup();
string treatment = designMap.get(group, mclass); //get value for this group in this category
string thisSub = designMap.get(group, subclass);
int numSigBeforeWilcox = significantOtuLabels.size();
+ if (m->debug) { m->mothurOut("[DEBUG]: completed Kruskal Wallis\n"); }
+
//check for subclass
string wilcoxString = "";
if ((subclass != "") && wilc) { significantOtuLabels = runWilcoxon(lookup, designMap, significantOtuLabels, class2SubClasses, subClass2GroupIndex, subclass2Class); wilcoxString += " ( " + toString(numSigBeforeWilcox) + " ) before internal wilcoxon"; }
int numSigAfterWilcox = significantOtuLabels.size();
+ if (m->debug) { m->mothurOut("[DEBUG]: completed Wilcoxon\n"); }
+
m->mothurOut("\nNumber of significantly discriminative features: " + toString(numSigAfterWilcox) + wilcoxString + ".\n");
map<int, double> sigOTUSLDA;
}
else { m->mothurOut("No features with significant differences between the classes.\n"); }
+ if (m->debug) { m->mothurOut("[DEBUG]: completed lda\n"); }
+
printResults(means, significantOtuLabels, sigOTUSLDA, lookup[0]->getLabel(), classes);
return 0;
}
for (int i = 0; i < lookup.size(); i++) {
- for (int j = 0; j < lookup[i]->getNumBins(); j++) { lookup[i]->set(j, lookup[i]->getAbundance(j)*mul[i], lookup[i]->getGroup()); }
+ for (int j = 0; j < lookup[i]->getNumBins(); j++) {
+ lookup[i]->set(j, lookup[i]->getAbundance(j)*mul[i], lookup[i]->getGroup());
+ }
}
return 0;
for (int i = 0; i < numBins; i++) {
if (m->control_pressed) { break; }
+ if (m->debug) { m->mothurOut("[DEBUG]: bin = " + toString(i) + "\n."); }
+
it = bins.find(i);
if (it != bins.end()) { //flagged in Kruskal Wallis and Wilcoxon(if we ran it)
+ if (m->debug) { m->mothurOut("[DEBUG]:flagged bin = " + toString(i) + "\n."); }
+
//fill x with this OTUs abundances
vector<double> x;
for (int j = 0; j < lookup.size(); j++) { x.push_back(lookup[j]->getAbundance(i)); }
//go through classes
for (map<string, vector<int> >::iterator it = class2GroupIndex.begin(); it != class2GroupIndex.end(); it++) {
+
+ if (m->debug) { m->mothurOut("[DEBUG]: class = " + it->first + "\n."); }
+
//max(float(feats['class'].count(c))*0.5,4)
//max(numGroups in this class*0.5, 4.0)
double necessaryNum = ((double)((it->second).size())*0.5);
minCl = (int)((float)(minCl*fBoots*fBoots*0.05));
minCl = max(minCl, 1);
+ if (m->debug) { m->mothurOut("[DEBUG]: about to start iters. \n."); }
+
vector< vector< vector<double> > > results;//[iters][numComparison][numOTUs]
for (int j = 0; j < iters; j++) {
if (m->control_pressed) { return sigOTUS; }
+ if (m->debug) { m->mothurOut("[DEBUG]: iter = " + toString(j) + "\n."); }
+
//find "good" random vector
vector<int> rand_s;
for (int h = 0; h < 1000; h++) { //generate a vector of length fractionNumGroups with range 0 to numGroups-1
projects / mothur.git / blobdiff