private void btnCompute_Click(object sender, EventArgs e)
{
bool bHasColumnHeaders = chkColumnHeaders.Checked;
bool bFullOutput = chkFullOutput.Checked;
bool bReportProgress = chkReportProgress.Checked;
bool bHuge = chkHuge.Checked;
FalseDiscoveryRate.PiMethod mPi = FalseDiscoveryRate.PiMethod.One;
if (cmbPIMethod.SelectedIndex == 0)
{
mPi = FalseDiscoveryRate.PiMethod.One;
}
else if (cmbPIMethod.SelectedIndex == 1)
{
mPi = FalseDiscoveryRate.PiMethod.WeightedSum;
}
if (cmbPIMethod.SelectedIndex == 2)
{
mPi = FalseDiscoveryRate.PiMethod.DoubleAverage;
}
if (chkFiltering.Checked)
{
mPi = FalseDiscoveryRate.PiMethod.Filtering;
}
double dCutoff = (double)udFDRCutoff.Value;
int cTableNamesColumns = (int)udNameColumns.Value - 1;
bool bPositiveFDR = chkPFDR.Checked;
bool bSampling = chkSampling.Checked;
bool bAutomatedSampling = false;
int iSampleSize = 0;
double dConvergenceEpsilon = 0.0;
if (bSampling)
{
iSampleSize = (int)udSampleSize.Value;
bAutomatedSampling = chkAutomatedSampling.Checked;
if (bAutomatedSampling)
{
dConvergenceEpsilon = 0.001;
}
}
string sInputFile = txtInputFile.Text;
string sOutputFile = txtOutputFile.Text;
DateTime dtBefore = DateTime.Now;
FalseDiscoveryRateComputationTask task = new FalseDiscoveryRateComputationTask(sInputFile, sOutputFile);
FalseDiscoveryRate t = new FalseDiscoveryRate(cTableNamesColumns, bReportProgress, dCutoff, bHuge, iSampleSize, dConvergenceEpsilon, bHasColumnHeaders, mPi, bPositiveFDR, bFullOutput, task);
task.setTask(t);
task.run();
DateTime dtAfter = DateTime.Now;
}
/*
* static void Main(string[] args)
* {
* DirectoryInfo dir = new DirectoryInfo( "D:\\fdr\\SyntheticMultiple" );
* FileInfo[] aFiles = dir.GetFiles();
* int iFile = 0, cFiles = aFiles.Length;
* foreach (FileInfo f in aFiles)
* {
* if (f.Name.StartsWith("synth") && f.Name.EndsWith(".txt"))
* {
* Console.WriteLine("Processing file " + iFile + " out of " + cFiles);
* FalseDiscoveryRate t = new FalseDiscoveryRate(1, true, double.PositiveInfinity, false, -1, 0.0, true, FalseDiscoveryRate.PiMethod.WeightedSum);
* t.computeFDR(f.FullName, f.FullName + ".FDR");
* iFile++;
* }
* }
* }
*/
static void Main(string[] args)
{
if (args.Length < 2)
{
Console.WriteLine("FisherExactTest utility for computing Fisher Exact Test and False Discovery Rate (FDR) for contingency tables.");
Console.WriteLine("Written by Guy Shani, Microsoft Research, October 2008.");
Console.WriteLine("Use the format: FisherExactTest inputfile outputfile <options>");
Console.WriteLine("inputfile - name of the text file containing the contingency table data. Each contingency table resides in a single row with the format a b c d, separateed by tabs.");
Console.WriteLine("outputfile - name of the text file where the results should be written.");
Console.WriteLine("Additional available options:");
Console.WriteLine("[-UseTableNames:<column count>] - each contingency table can be perceeded by table names columns. Use this option to set the number of columns perceeding each table. The default is 0 - no table names.");
Console.WriteLine("[-SilentMode] - execute the application without any progress messages.");
Console.WriteLine("[-FDRCutoff:x] - Allows to avoid outputing tables with an FDR exciding the threshold x.");
Console.WriteLine("[-Huge] - When the input data is huge (more than 100K tables) this option avoids several caching procedures to allow handling more data.");
Console.WriteLine("[-UseSampling[:n]] - Computes FDRs using only n sampled tables. Default value for n is 100K.");
Console.WriteLine("[-AutomatedSampling[:d]] - Activates the automated sampling algorithm, computing FDRs repeatedly with increasing sample sizes until the largest change in FDR drops below d. Default value for d is 0.1.");
Console.WriteLine("[-ColumnHeaders] - use when the input files has column headers.");
Console.WriteLine("[-EvaluatePi] - by default pi0=1, set this parameter to evaluate pi0=sum(observed p-values)/sum(null p-values).");
Console.WriteLine("[-Filtering] - Computes pi0 using only relevant tables. This flag supersedes the EvaluatePi flag.");
Console.WriteLine("[-FullOutput] - outputs all the statistics that were computed. By default only p-values and q-values are written to the output file.");
Console.WriteLine("[-pFDR] - Compute positive FDR. The default is to compute FDR rather than pFDR.");
}
else
{
string sInputFileName = args[0];
string sOutputFileName = args[1];
int cTableNamesColumns = 0;
bool bReportProgress = (findArgument(args, "-SilentMode") == -1);
bool bHuge = (findArgument(args, "-Huge") != -1);
double dCutoff = double.PositiveInfinity;
int iSampleSize = -1;
double dMinimalChangeBetweenSamples = -1.0;
bool bHasColumnHeaders = false;
FalseDiscoveryRate.PiMethod mPi = FalseDiscoveryRate.PiMethod.One;
bool bFullOutput = false;
bool bPositiveFDR = false;
int iColumnHeaders = findArgument(args, "-ColumnHeaders");
if (iColumnHeaders != -1)
{
bHasColumnHeaders = true;
}
int iFullOutput = findArgument(args, "-FullOutput");
if (iFullOutput != -1)
{
bFullOutput = true;
}
int iPFDR = findArgument(args, "-pFDR");
if (iPFDR != -1)
{
bPositiveFDR = true;
}
int iEvaluatePi = findArgument(args, "-EvaluatePi");
if (iEvaluatePi != -1)
{
mPi = FalseDiscoveryRate.PiMethod.WeightedSum;
}
iEvaluatePi = findArgument(args, "-Filtering");
if (iEvaluatePi != -1)
{
mPi = FalseDiscoveryRate.PiMethod.Filtering;
}
int iCutoff = findArgument(args, "-FDRCutoff");
if (iCutoff != -1)
{
int idx = args[iCutoff].IndexOf(':');
dCutoff = double.Parse(args[iCutoff].Substring(idx + 1));
}
int iTableNames = findArgument(args, "-UseTableNames");
if (iTableNames != -1)
{
int idx = args[iTableNames].IndexOf(':');
cTableNamesColumns = int.Parse(args[iTableNames].Substring(idx + 1));
}
int iSampling = findArgument(args, "-UseSampling");
if (iSampling != -1)
{
int idx = args[iSampling].IndexOf(':');
if (idx > 0)
{
iSampleSize = int.Parse(args[iSampling].Substring(idx + 1));
}
else
{
iSampleSize = 100000;
}
}
int iAutomatedSampling = findArgument(args, "-AutomatedSampling");
if (iAutomatedSampling != -1)
{
int idx = args[iAutomatedSampling].IndexOf(':');
if (iSampleSize == -1)
{
iSampleSize = 100000;
}
if (idx < 0)
{
dMinimalChangeBetweenSamples = 0.01;
}
else
{
dMinimalChangeBetweenSamples = double.Parse(args[iAutomatedSampling].Substring(idx + 1));
}
}
DateTime dtBefore = DateTime.Now;
ProgressReport pr = new ConsoleProgressReport();
FalseDiscoveryRate t = new FalseDiscoveryRate(cTableNamesColumns, bReportProgress, dCutoff, bHuge, iSampleSize, dMinimalChangeBetweenSamples, bHasColumnHeaders, mPi, bPositiveFDR, bFullOutput, pr);
t.computeFDR(sInputFileName, sOutputFileName);
DateTime dtAfter = DateTime.Now;
if (bReportProgress)
{
Console.WriteLine("Total execution time " + dtAfter.Subtract(dtBefore));
}
}
}
