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A78434891162224F00100BE0 /* chimeraccodecommand.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; path = chimeraccodecommand.cpp; sourceTree = "<group>"; };
+ A7BBDA7B11B5694E006E6551 /* classifyotucommand.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = classifyotucommand.h; sourceTree = "<group>"; };
+ A7BBDA7C11B5694E006E6551 /* classifyotucommand.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; path = classifyotucommand.cpp; sourceTree = "<group>"; };
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A7D215C911996C6E00F13F13 /* clearcutcommand.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; path = clearcutcommand.cpp; sourceTree = "<group>"; };
A7D216061199C47F00F13F13 /* catchallcommand.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = catchallcommand.h; sourceTree = "<group>"; };
A73953DB11987ED100B0B160 /* chopseqscommand.cpp */,
A7DA201E113FECD400BF472F /* classifyseqscommand.h */,
A7DA201D113FECD400BF472F /* classifyseqscommand.cpp */,
+ A7BBDA7B11B5694E006E6551 /* classifyotucommand.h */,
+ A7BBDA7C11B5694E006E6551 /* classifyotucommand.cpp */,
A7D215C811996C6E00F13F13 /* clearcutcommand.h */,
A7D215C911996C6E00F13F13 /* clearcutcommand.cpp */,
A7DA2021113FECD400BF472F /* clustercommand.cpp */,
A7DA205D113FECD400BF472F /* getlabelcommand.h */,
A7DA205E113FECD400BF472F /* getlistcountcommand.cpp */,
A7DA205F113FECD400BF472F /* getlistcountcommand.h */,
- A7DA2060113FECD400BF472F /* getoturepcommand.cpp */,
A7DA2061113FECD400BF472F /* getoturepcommand.h */,
+ A7DA2060113FECD400BF472F /* getoturepcommand.cpp */,
A7DA2062113FECD400BF472F /* getrabundcommand.cpp */,
A7DA2063113FECD400BF472F /* getrabundcommand.h */,
A7DA2064113FECD400BF472F /* getsabundcommand.cpp */,
m->mothurOut("The name parameter allows you add a names file with your taxonomy file.\n");
m->mothurOut("The label parameter allows you to select what distance levels you would like a output files created for, and is separated by dashes.\n");
m->mothurOut("The default value for label is all labels in your inputfile.\n");
- m->mothurOut("The cutoff parameter allows you to specify a concensus confidence threshold for your taxonomy. The default is 51, meaning 51%. Cutoff cannot be below 51.\n");
- m->mothurOut("The probs parameter shuts off the outputting of the concensus confidence results. The default is true, meaning you want the confidence to be shown.\n");
+ m->mothurOut("The cutoff parameter allows you to specify a consensus confidence threshold for your taxonomy. The default is 51, meaning 51%. Cutoff cannot be below 51.\n");
+ m->mothurOut("The probs parameter shuts off the outputting of the consensus confidence results. The default is true, meaning you want the confidence to be shown.\n");
m->mothurOut("The classify.otu command should be in the following format: classify.otu(taxonomy=yourTaxonomyFile, list=yourListFile, name=yourNamesFile, label=yourLabels).\n");
m->mothurOut("Example classify.otu(taxonomy=abrecovery.silva.full.taxonomy, list=abrecovery.fn.list, label=0.10).\n");
m->mothurOut("Note: No spaces between parameter labels (i.e. list), '=' and parameters (i.e.yourListFile).\n\n");
}
}
//**********************************************************************************************************************
-string ClassifyOtuCommand::findConcensusTaxonomy(int bin, ListVector* thisList, int& size) {
+string ClassifyOtuCommand::findConsensusTaxonomy(int bin, ListVector* thisList, int& size) {
try{
string conTax = "";
vector<string> names;
it = taxMap.find(names[i]);
if (it == taxMap.end()) { //this name is not in taxonomy file, skip it
- m->mothurOut(names[i] + " is not in your taxonomy file. I will not include it in the concensus."); m->mothurOutEndLine();
+ m->mothurOut(names[i] + " is not in your taxonomy file. I will not include it in the consensus."); m->mothurOutEndLine();
}else{
//if namesfile include the names
it2 = nameMap.find(names[i]);
if (it2 == nameMap.end()) { //this name is not in name file, skip it
- m->mothurOut(names[i] + " is not in your name file. I will not include it in the concensus."); m->mothurOutEndLine();
+ m->mothurOut(names[i] + " is not in your name file. I will not include it in the consensus."); m->mothurOutEndLine();
}else{
vector<string> nameFileNames;
}
//is this taxonomy above cutoff
- int concensusConfidence = ceil((bestChildSize / (float) size) * 100);
+ int consensusConfidence = ceil((bestChildSize / (float) size) * 100);
- if (concensusConfidence >= cutoff) { //if yes, add it
+ if (consensusConfidence >= cutoff) { //if yes, add it
if (probs) {
- conTax += bestChild.name + "(" + toString(concensusConfidence) + ");";
+ conTax += bestChild.name + "(" + toString(consensusConfidence) + ");";
}else{
conTax += bestChild.name + ";";
}
}
catch(exception& e) {
- m->errorOut(e, "ClassifyOtuCommand", "findConcensusTaxonomy");
+ m->errorOut(e, "ClassifyOtuCommand", "findConsensusTaxonomy");
exit(1);
}
}
//for each bin in the list vector
for (int i = 0; i < processList->getNumBins(); i++) {
- conTax = findConcensusTaxonomy(i, processList, size);
+ conTax = findConsensusTaxonomy(i, processList, size);
if (m->control_pressed) { out.close(); return 0; }
int readTaxonomyFile();
void removeConfidences(string&);
int process(ListVector*);
- string findConcensusTaxonomy(int, ListVector*, int&); // returns the name of the "representative" taxonomy of given bin
+ string findConsensusTaxonomy(int, ListVector*, int&); // returns the name of the "representative" taxonomy of given bin
};
m->mothurOut("The gapextend parameter allows you to specify the penalty for extending a gap in an alignment. The default is -1.0.\n");
m->mothurOut("The numwanted parameter allows you to specify the number of sequence matches you want with the knn method. The default is 10.\n");
m->mothurOut("The cutoff parameter allows you to specify a bootstrap confidence threshold for your taxonomy. The default is 0.\n");
- m->mothurOut("The probs parameter shut off the bootstrapping results for the bayesian method. The default is true, meaning you want the bootstrapping to be run.\n");
+ m->mothurOut("The probs parameter shuts off the bootstrapping results for the bayesian method. The default is true, meaning you want the bootstrapping to be shown.\n");
m->mothurOut("The iters parameter allows you to specify how many iterations to do when calculating the bootstrap confidence score for your taxonomy with the bayesian method. The default is 100.\n");
m->mothurOut("The classify.seqs command should be in the following format: \n");
m->mothurOut("classify.seqs(template=yourTemplateFile, fasta=yourFastaFile, method=yourClassificationMethod, search=yourSearchmethod, ksize=yourKmerSize, taxonomy=yourTaxonomyFile, processors=yourProcessors) \n");
#include "catchallcommand.h"
#include "splitabundcommand.h"
#include "clustersplitcommand.h"
+#include "classifyotucommand.h"
/*******************************************************/
commands["catchall"] = "catchall";
commands["split.abund"] = "split.abund";
commands["cluster.split"] = "cluster.split";
+ commands["classify.otu"] = "classify.otu";
commands["classify.seqs"] = "MPIEnabled";
commands["dist.seqs"] = "MPIEnabled";
commands["filter.seqs"] = "MPIEnabled";
else if(commandName == "catchall") { command = new CatchAllCommand(optionString); }
else if(commandName == "split.abund") { command = new SplitAbundCommand(optionString); }
else if(commandName == "cluster.split") { command = new ClusterSplitCommand(optionString); }
+ else if(commandName == "classify.otu") { command = new ClassifyOtuCommand(optionString); }
else { command = new NoCommand(optionString); }
return command;
/***********************************************************************/
void CommandFactory::printCommands(ostream& out) {
try {
- out << "Valid commands are ";
+ out << "Valid commands are: ";
for (it = commands.begin(); it != commands.end(); it++) {
- out << it->first << ", ";
+ out << it->first << ",";
}
out << endl;
}
-L../readline-6.0\r
endif\r
\r
-USEMPI ?= yes\r
+USEMPI ?= no\r
\r
ifeq ($(strip $(USEMPI)),yes)\r
CC = mpic++\r
./taxonomyequalizer.o\\r
./phylotypecommand.o\\r
./classifyseqscommand.o\\r
+ ./classifyotucommand.o\\r
./parsesffcommand.o\\r
./classify.o\\r
./phylotree.o\\r
./taxonomyequalizer.o\\r
./phylotypecommand.o\\r
./classifyseqscommand.o\\r
+ ./classifyotucommand.o\\r
./parsesffcommand.o\\r
./classify.o\\r
./phylotree.o\\r
./taxonomyequalizer.o\\r
./phylotypecommand.o\\r
./classifyseqscommand.o\\r
+ ./classifyotucommand.o\\r
./parsesffcommand.o\\r
./classify.o\\r
./phylotree.o\\r
# Item # 207 -- splitmatrix --\r
./clustersplitcommand.o : clustersplitcommand.cpp\r
$(CC) $(CC_OPTIONS) clustersplitcommand.cpp -c $(INCLUDE) -o ./clustersplitcommand.o\r
+ \r
+# Item # 207 -- splitmatrix --\r
+./classifyotucommand.o : classifyotucommand.cpp\r
+ $(CC) $(CC_OPTIONS) classifyotucommand.cpp -c $(INCLUDE) -o ./classifyotucommand.o\r
+\r
\r
##### END RUN ####\r
projects / mothur.git / commitdiff