//Engine.Evaluate($"png('{ImagePath.Replace('\\', '/') + imagePath + ".png"}', {900}, {600})");
internal static double[] GenerateNormalDistribution(double min, double max, int numberOfFeatures)
{
try
{
/* Engine.Evaluate($"rnorm.between <- function(n, minimum = 0, maximum = 1)");
* Engine.Evaluate("{");
* Engine.Evaluate($"x <- rnorm(n)");
* Engine.Evaluate($"max_x <- max(x)");
* Engine.Evaluate($"min_x <- min(x)");
* Engine.Evaluate($"x <- x - min_x");
* Engine.Evaluate($"x <- x / (max_x - min_x)");
* Engine.Evaluate($"x <- x * (maximum - minimum)");
* Engine.Evaluate($"x <- x + minimum");
* Engine.Evaluate($"return (x)");
* Engine.Evaluate("}");
*/
//var func = Engine.Evaluate("function (n, min, max) {x <- rnorm(n, mean = 0, sd = 1); x <- x - -3; x <- x / (6); x <- x * (min - max); y <- x + min; return (y) }").AsFunction();
var func = Engine.Evaluate(@"function (n, min, max) {
x <- rnorm(n, mean = 0, sd = 1)
x <- x - -3
x <- x / (6)
x <- x * (max - min)
x <- x + min
return (x)
}").AsFunction();
var param1 = Engine.CreateInteger(numberOfFeatures);
var param2 = Engine.CreateNumeric(min);
var param3 = Engine.CreateNumeric(max);
return(func.Invoke(new SymbolicExpression[] { param1, param2, param3 }).AsNumeric().ToArray());
//return Engine.Evaluate($"result <- rnorm.between({numberOfFeatures}, {min}, {max})").AsNumeric().ToArray();
}
catch (Exception e)
{ Console.WriteLine(e.ToString()); return(new double[] { 0 }); }
}
static void Main(string[] args)
{
REngine.SetEnvironmentVariables();
// There are several options to initialize the engine, but by default the following suffice:
REngine engine = REngine.GetInstance();
//engine.Birth_of_age();
//engine.Age_title_colours();
//engine.Barchart();
//engine.barchart_months_revenue();
//engine.Barchart_stacked();
engine.SetWd();
engine.GetWd();
//engine.Print("开始安装exec组件");
//engine.Evaluate("install.packages('xlsx')");
//engine.Print("结束安装exec组件");
engine.Print("读取文件开始");
//var csvName = engine.ReadCsv("InputName.csv");
//var param = new SymbolicExpressionParamList() { IsUseParamName = false };
//param.Add(new SymbolicExpressionParam(csvName));
//param.Add(new SymbolicExpressionParam(where: " as.Date(start_date) > as.Date('2014-01-01') "));
////param.Add(new SymbolicExpressionParam(where: "salary>600&dept=='IT'"));
//var subset = engine.ExecFunction(param, "subset");
//var paramA = new SymbolicExpressionParamList() { IsUseParamName = false };
//paramA.Add(new SymbolicExpressionParam(subset.AsDataFrame()));
//paramA.Add(new SymbolicExpressionParam(where: "'output1.csv'"));
//paramA.Add(new SymbolicExpressionParam(where: "row.names = FALSE"));
//engine.ExecFunction(paramA, "write.csv");
//engine.ReadCsv("output1.csv");
engine.Evaluate("library(xlsx) ");
var paramA = new SymbolicExpressionParamList()
{
IsUseParamName = false
};
paramA.Add(new SymbolicExpressionParam(where : "'input.xlsx'"));
paramA.Add(new SymbolicExpressionParam(engine.CreateNumeric(1), paramName: "sheetIndex"));
engine.ExecFunction(paramA, "read.xlsx");
//engine.ReadCsv("output1.csv");
engine.Print("读取文件结束");
engine.Dispose();
Console.ReadKey();
}
private void SetupDotNetToRConverters()
{
SetupDotNetToRConverter(typeof(void), p => null);
SetupDotNetToRConverter(typeof(string), p => engine.CreateCharacter((string)p));
SetupDotNetToRConverter(typeof(string[]), p => engine.CreateCharacterVector((string[])p));
SetupDotNetToRConverter(typeof(List <string>), p => engine.CreateCharacterVector((IEnumerable <string>)p));
SetupDotNetToRConverter(typeof(IList <string>), p => engine.CreateCharacterVector((IEnumerable <string>)p));
SetupDotNetToRConverter(typeof(ICollection <string>), p => engine.CreateCharacterVector((IEnumerable <string>)p));
SetupDotNetToRConverter(typeof(IEnumerable <string>), p => engine.CreateCharacterVector((IEnumerable <string>)p));
SetupDotNetToRConverter(typeof(string[, ]), p => engine.CreateCharacterMatrix((string[, ])p));
SetupDotNetToRConverter(typeof(int), p => engine.CreateInteger((int)p));
SetupDotNetToRConverter(typeof(int[]), p => engine.CreateIntegerVector((int[])p));
SetupDotNetToRConverter(typeof(List <int>), p => engine.CreateIntegerVector((IEnumerable <int>)p));
SetupDotNetToRConverter(typeof(IList <int>), p => engine.CreateIntegerVector((IEnumerable <int>)p));
SetupDotNetToRConverter(typeof(ICollection <int>), p => engine.CreateIntegerVector((IEnumerable <int>)p));
SetupDotNetToRConverter(typeof(IEnumerable <int>), p => engine.CreateIntegerVector((IEnumerable <int>)p));
SetupDotNetToRConverter(typeof(int[, ]), p => engine.CreateIntegerMatrix((int[, ])p));
SetupDotNetToRConverter(typeof(bool), p => engine.CreateLogical((bool)p));
SetupDotNetToRConverter(typeof(bool[]), p => engine.CreateLogicalVector((bool[])p));
SetupDotNetToRConverter(typeof(List <bool>), p => engine.CreateLogicalVector((IEnumerable <bool>)p));
SetupDotNetToRConverter(typeof(IList <bool>), p => engine.CreateLogicalVector((IEnumerable <bool>)p));
SetupDotNetToRConverter(typeof(ICollection <bool>), p => engine.CreateLogicalVector((IEnumerable <bool>)p));
SetupDotNetToRConverter(typeof(IEnumerable <bool>), p => engine.CreateLogicalVector((IEnumerable <bool>)p));
SetupDotNetToRConverter(typeof(bool[, ]), p => engine.CreateLogicalMatrix((bool[, ])p));
SetupDotNetToRConverter(typeof(double), p => engine.CreateNumeric((double)p));
SetupDotNetToRConverter(typeof(double[]), p => engine.CreateNumericVector((double[])p));
SetupDotNetToRConverter(typeof(List <double>), p => engine.CreateNumericVector((IEnumerable <double>)p));
SetupDotNetToRConverter(typeof(IList <double>), p => engine.CreateNumericVector((IEnumerable <double>)p));
SetupDotNetToRConverter(typeof(ICollection <double>), p => engine.CreateNumericVector((IEnumerable <double>)p));
SetupDotNetToRConverter(typeof(IEnumerable <double>), p => engine.CreateNumericVector((IEnumerable <double>)p));
SetupDotNetToRConverter(typeof(double[, ]), p => engine.CreateNumericMatrix((double[, ])p));
SetupDotNetToRConverter(typeof(DateTime), p => engine.CreatePosixct((DateTime)p));
SetupDotNetToRConverter(typeof(DateTime[]), p => engine.CreatePosixctVector((DateTime[])p));
SetupDotNetToRConverter(typeof(List <DateTime>), p => engine.CreatePosixctVector((IEnumerable <DateTime>)p));
SetupDotNetToRConverter(typeof(IList <DateTime>), p => engine.CreatePosixctVector((IEnumerable <DateTime>)p));
SetupDotNetToRConverter(typeof(ICollection <DateTime>), p => engine.CreatePosixctVector((IEnumerable <DateTime>)p));
SetupDotNetToRConverter(typeof(IEnumerable <DateTime>), p => engine.CreatePosixctVector((IEnumerable <DateTime>)p));
SetupDotNetToRConverter(typeof(DateTime[, ]), p => engine.CreatePosixctMatrix((DateTime[, ])p));
SetupDotNetToRConverter(typeof(TimeSpan), p => engine.CreateDiffTime((TimeSpan)p));
SetupDotNetToRConverter(typeof(TimeSpan[]), p => engine.CreateDiffTimeVector((TimeSpan[])p));
SetupDotNetToRConverter(typeof(List <TimeSpan>), p => engine.CreateDiffTimeVector((IEnumerable <TimeSpan>)p));
SetupDotNetToRConverter(typeof(IList <TimeSpan>), p => engine.CreateDiffTimeVector((IEnumerable <TimeSpan>)p));
SetupDotNetToRConverter(typeof(ICollection <TimeSpan>), p => engine.CreateDiffTimeVector((IEnumerable <TimeSpan>)p));
SetupDotNetToRConverter(typeof(IEnumerable <TimeSpan>), p => engine.CreateDiffTimeVector((IEnumerable <TimeSpan>)p));
SetupDotNetToRConverter(typeof(TimeSpan[, ]), p => engine.CreateDiffTimeMatrix((TimeSpan[, ])p));
}
public override void SetSymbol(REngine rEngine, string name, object value)
{
rEngine.SetSymbol(name, rEngine.CreateNumeric((double)value));
}
private void button3_Click(object sender, EventArgs e)
{
string filePath = this.textBox2.Text;
DataTable dt = new DataTable();
FileStream fs = new FileStream(filePath, System.IO.FileMode.Open, System.IO.FileAccess.Read);
StreamReader sr = new StreamReader(fs, Encoding.UTF8);
string strLine = "";
string[] aryLine = null;
string[] tableHead = null;
int columnCount = 0;
bool IsFirst = true;
while ((strLine = sr.ReadLine()) != null)
{
if (IsFirst == true)
{
tableHead = strLine.Split('\t');
IsFirst = false;
columnCount = tableHead.Length;
for (int i = 0; i < columnCount; i++)
{
tableHead[i] = tableHead[i].Replace("\"", "");
DataColumn dc = new DataColumn(tableHead[i]);
dt.Columns.Add(dc);
}
}
else
{
aryLine = strLine.Split('\t');
DataRow dr = dt.NewRow();
for (int j = 0; j < columnCount; j++)
{
dr[j] = aryLine[j].Replace("\"", "");
}
dt.Rows.Add(dr);
}
}
sr.Close();
fs.Close();
app.EFProfile = dt;
app.FactorName = new string[app.EFProfile.Columns.Count - 1];
for (int i = 0; i < app.EFProfile.Columns.Count - 1; i++)
{
app.FactorName[i] = app.EFProfile.Columns[i + 1].ColumnName;
}
int FactorNum = app.FactorName.GetLength(0);
int SampleNum = app.EFProfile.Rows.Count;
app.EFMatrix = new double[SampleNum, FactorNum];
for (int i = 0; i < SampleNum; i++)
{
for (int j = 0; j < FactorNum; j++)
{
app.EFMatrix[i, j] = Convert.ToDouble(app.EFProfile.Rows[i][j + 1]);
}
}
app.Allid = new List <List <int> >();
app.pvalue = new List <List <double> >();
app.Rvalue = new List <List <double> >();
app.Fvalue = new List <double>();
float alpha = float.Parse(this.textBox1.Text.ToString());
app.alphaen = alpha;
if ((app.EFMatrix == null) || (app.SamName.GetLength(0) != SampleNum))
{
MessageBox.Show("No Environmental Factors information or improper Environmental Factors information!!", "Warning!!!", MessageBoxButtons.OK);
}
else
{
REngine.SetEnvironmentVariables();
REngine EF = REngine.GetInstance();
EF.Initialize();
if (this.checkBox1.Checked)
{
app.FinalFactorCount = new List <List <double> >();
app.FinalFactorName = new List <string>();
for (int i = 0; i < app.EFMatrix.GetLength(0); i++)
{
List <double> rowfactor = new List <double>();
for (int j = 0; j < app.EFMatrix.GetLength(1); j++)
{
rowfactor.Add(app.EFMatrix[i, j]);
}
for (int j = 0; j < app.EFMatrix.GetLength(1) - 1; j++)
{
for (int k = j + 1; k < app.EFMatrix.GetLength(1); k++)
{
rowfactor.Add(app.EFMatrix[i, j] * app.EFMatrix[i, k]);
}
}
app.FinalFactorCount.Add(rowfactor);
}
for (int i = 0; i < app.FactorName.GetLength(0); i++)
{
app.FinalFactorName.Add(app.FactorName[i]);
}
for (int i = 0; i < app.FactorName.GetLength(0); i++)
{
for (int j = i + 1; j < app.FactorName.GetLength(0); j++)
{
app.FinalFactorName.Add(app.FactorName[i] + "&" + app.FactorName[j]);
}
}
}
else
{
app.FinalFactorCount = new List <List <double> >();
app.FinalFactorName = new List <string>();
for (int i = 0; i < app.EFMatrix.GetLength(0); i++)
{
List <double> rowfactor = new List <double>();
for (int j = 0; j < app.EFMatrix.GetLength(1); j++)
{
rowfactor.Add(app.EFMatrix[i, j]);
}
app.FinalFactorCount.Add(rowfactor);
}
for (int i = 0; i < app.FactorName.GetLength(0); i++)
{
app.FinalFactorName.Add(app.FactorName[i]);
}
}
double[][] Factortemp = new double[app.FinalFactorCount.Count][];
for (int i = 0; i < app.FinalFactorCount.Count; i++)
{
Factortemp[i] = new double[app.FinalFactorCount[i].Count];
for (int j = 0; j < app.FinalFactorCount[i].Count; j++)
{
Factortemp[i][j] = app.FinalFactorCount[i][j];
}
}
double[][] TFactorCount = app.TMatrix(Factortemp);
for (int i = 0; i < TFactorCount.GetLength(0); i++)
{
double mean = app.MEAN(TFactorCount[i]);
double sd = app.sd(TFactorCount[i]);
for (int j = 0; j < TFactorCount[i].GetLength(0); j++)
{
TFactorCount[i][j] = (TFactorCount[i][j] - mean) / sd;
}
}
double[][] Factor = app.TMatrix(TFactorCount);
int n = Factor.GetLength(0);
for (int i = 1; i < n; i++)
{
EF.SetSymbol("alpha", EF.CreateNumeric(alpha));
EF.SetSymbol("df1value", EF.CreateNumeric(1));
EF.SetSymbol("df2value", EF.CreateNumeric(i));
EF.Evaluate("Fvalue <- qf(1 - alpha ,df1 = df1value ,df2 = df2value)");
app.Fvalue.Add(EF.GetSymbol("Fvalue").AsNumeric().First());
}
for (int l = 0; l < app.FeaName.GetLength(0); l++)
{
double[] Ynor = new double[app.SamName.GetLength(0)];
for (int i = 0; i < Ynor.GetLength(0); i++)
{
Ynor[i] = app.CountMatrix[l, i];
}
double mean = app.MEAN(Ynor);
double sd = app.sd(Ynor);
for (int i = 0; i < Ynor.GetLength(0); i++)
{
Ynor[i] = (Ynor[i] - mean) / sd;
}
double[][] Y = new double[app.SamName.GetLength(0)][];
for (int i = 0; i < app.SamName.GetLength(0); i++)
{
Y[i] = new double[1];
Y[i][0] = Ynor[i];
}
List <int> idNum = new List <int>();
List <double> rowP = new List <double>();
List <double> rowR = new List <double>();
double[][] whole = new double[Factor.GetLength(0)][];
for (int i = 0; i < whole.GetLength(0); i++)
{
whole[i] = new double[Factor[i].GetLength(0) + 1];
for (int j = 0; j < Factor[i].GetLength(0); j++)
{
whole[i][j] = Factor[i][j];
}
whole[i][Factor[i].GetLength(0)] = Y[i][0];
}
double[][] Rmatrix = new double[Factor[0].GetLength(0) + 1][];
for (int i = 0; i < Rmatrix.GetLength(0); i++)
{
Rmatrix[i] = new double[Rmatrix.GetLength(0)];
}
Rmatrix = app.Cormatrix(whole);
while (app.Add_Factors(Factor, Y, alpha, Rmatrix, idNum) != 0)
{
int addindex = app.Add_Factors(Factor, Y, alpha, Rmatrix, idNum);
idNum.Add(addindex);
Rmatrix = app.Rconvert(Rmatrix, addindex);
if (app.Delete_Factors(Factor, Y, alpha, Rmatrix, idNum) != 0)
{
int deletindex = app.Delete_Factors(Factor, Y, alpha, Rmatrix, idNum);
for (int i = 0; i < idNum.Count; i++)
{
if (idNum[i] == deletindex)
{
idNum.RemoveAt(i);
}
}
Rmatrix = app.Rconvert(Rmatrix, deletindex);
while (app.Check_Factors(Factor, Y, alpha, Rmatrix, idNum) != 0)
{
deletindex = app.Check_Factors(Factor, Y, alpha, Rmatrix, idNum);
for (int i = 0; i < idNum.Count; i++)
{
if (idNum[i] == deletindex)
{
idNum.RemoveAt(i);
}
}
Rmatrix = app.Rconvert(Rmatrix, deletindex);
}
}
}
int p = idNum.Count;
for (int i = 0; i < idNum.Count; i++)
{
double u = Math.Pow(Rmatrix[idNum[i] - 1][Rmatrix[0].GetLength(0) - 1], 2) / Rmatrix[idNum[i] - 1][idNum[i] - 1];
double f = u / (Rmatrix[Rmatrix.GetLength(0) - 1][Rmatrix[0].GetLength(0) - 1] / (n - p - 1));
EF.SetSymbol("Fvalue", EF.CreateNumeric(f));
EF.SetSymbol("df1value", EF.CreateNumeric(1));
EF.SetSymbol("df2value", EF.CreateNumeric(n - p - 1));
EF.Evaluate("pvalue <- 1 - pf(Fvalue , df1 = df1value , df2 = df2value)");
rowP.Add(EF.GetSymbol("pvalue").AsNumeric().First());
double[] x = new double[n];
double[] y = new double[n];
double[] xy = new double[n];
double[] xx = new double[n];
double[] yy = new double[n];
for (int k = 0; k < n; k++)
{
x[k] = app.FinalFactorCount[k][idNum[i] - 1];
y[k] = app.CountMatrix[l, k];
xx[k] = app.FinalFactorCount[k][idNum[i] - 1] * app.FinalFactorCount[k][idNum[i] - 1];
yy[k] = app.CountMatrix[l, k] * app.CountMatrix[l, k];
xy[k] = app.FinalFactorCount[k][idNum[i] - 1] * app.CountMatrix[l, k];
}
double R = (app.MEAN(xy) - app.MEAN(x) * app.MEAN(y)) / Math.Sqrt((app.MEAN(xx) - app.MEAN(x) * app.MEAN(x)) * (app.MEAN(yy) - app.MEAN(y) * app.MEAN(y)));
double R_square = R * R;
rowR.Add(R_square);
}
app.Allid.Add(idNum);
app.pvalue.Add(rowP);
app.Rvalue.Add(rowR);
}
app.B = new double[app.FeaName.GetLength(0)][][];
for (int i = 0; i < app.FeaName.GetLength(0); i++)
{
app.B[i] = new double[app.FinalFactorName.Count + 1][];
for (int j = 0; j < app.FinalFactorName.Count + 1; j++)
{
app.B[i][j] = new double[1];
}
}
app.T = new double[app.FeaName.GetLength(0)][];
for (int i = 0; i < app.FeaName.GetLength(0); i++)
{
app.T[i] = new double[app.FinalFactorName.Count + 1];
}
app.P = new double[app.FeaName.GetLength(0)];
app.R_square = new double[app.FeaName.GetLength(0)];
for (int j = 0; j < app.FeaName.GetLength(0); j++)
{
if (app.Allid[j].Count != 0)
{
double[][] X = new double[app.FinalFactorCount.Count][];
for (int i = 0; i < X.Length; i++)
{
X[i] = new double[app.Allid[j].Count + 1];
X[i][0] = 1;
for (int k = 1; k <= app.Allid[j].Count; k++)
{
X[i][k] = app.FinalFactorCount[i][app.Allid[j][k - 1] - 1];
}
}
double[][] Y = new double[app.SamName.GetLength(0)][];
for (int i = 0; i < app.SamName.GetLength(0); i++)
{
Y[i] = new double[1];
Y[i][0] = app.CountMatrix[j, i];
}
double[][] B = new double[app.FinalFactorName.Count + 1][];
for (int i = 0; i < app.FinalFactorName.Count + 1; i++)
{
B[i] = new double[1];
}
double[][] C = new double[app.FinalFactorName.Count + 1][];
for (int i = 0; i < app.FinalFactorName.Count + 1; i++)
{
C[i] = new double[app.FinalFactorName.Count + 1];
}
double[][] E = new double[app.SamName.GetLength(0)][];
for (int i = 0; i < app.SamName.GetLength(0); i++)
{
E[i] = new double[1];
}
C = app.InverseMatrix(app.MultipleMatrix(app.TMatrix(X), X));
B = app.MultipleMatrix(app.MultipleMatrix(C, app.TMatrix(X)), Y);
app.B[j] = B;
E = app.MinusMatrix(Y, app.MultipleMatrix(X, B));
double sigma = 0;
for (int i = 0; i < app.SamName.GetLength(0); i++)
{
sigma = sigma + Math.Pow(E[i][0], 2);
}
sigma = Math.Sqrt(sigma / (app.SamName.GetLength(0) - app.FactorName.GetLength(0) - 1));
for (int i = 0; i < app.Allid[j].Count + 1; i++)
{
app.T[j][i] = Math.Abs(B[i][0] / (sigma * Math.Sqrt(C[i][i])));
}
double y_mean = 0;
double[][] y_predict = new double[app.SamName.GetLength(0)][];
for (int i = 0; i < app.SamName.GetLength(0); i++)
{
y_predict[i] = new double[1];
}
for (int i = 0; i < app.SamName.GetLength(0); i++)
{
y_mean = y_mean + Y[i][0];
}
y_mean = y_mean / (app.SamName.GetLength(0));
y_predict = app.MultipleMatrix(X, B);
double SSR = 0;
double SSE = 0;
for (int i = 0; i < app.SamName.GetLength(0); i++)
{
SSR = SSR + Math.Pow((y_predict[i][0] - y_mean), 2);
}
for (int i = 0; i < app.SamName.GetLength(0); i++)
{
SSE = SSE + Math.Pow((Y[i][0] - y_predict[i][0]), 2);
}
double F = (SSR / (app.FinalFactorName.Count)) / (SSE / (app.SamName.GetLength(0) - app.FinalFactorName.Count - 1));
int p = app.Allid[j].Count;
EF.SetSymbol("Fvalue", EF.CreateNumeric(F));
EF.SetSymbol("df1value", EF.CreateNumeric(p));
EF.SetSymbol("df2value", EF.CreateNumeric(n - p - 1));
EF.Evaluate("pvalue_whole <- 1 - pf(Fvalue , df1 = df1value , df2 = df2value)");
app.P[j] = EF.GetSymbol("pvalue_whole").AsNumeric().First();
double SST = SSR + SSE;
app.R_square[j] = SSR / SST;
if (app.P[j] >= alpha)
{
app.P[j] = 2;
app.R_square[j] = 2;
}
}
else
{
app.P[j] = 2;
app.R_square[j] = 2;
}
}
app.EFAcheck = this.checkBox2.Checked;
app.EFAradio1 = this.radioButton1.Checked;
app.EFAradio2 = this.radioButton2.Checked;
Environment_Output f14 = new Environment_Output();
f14.MdiParent = this.MdiParent;
f14.Show();
this.Close();
}
}
private void button4_Click(object sender, EventArgs e)
{
int FeatureNum = app.FeaName.GetLength(0);
int SampleNum = app.SamName.GetLength(0);
List <double> prob = new List <double>();
List <double> stat = new List <double>();
List <double> pvalue = new List <double>();
double[] bonferroni = new double[FeatureNum];
double[] fdr = new double[FeatureNum];
//int length;
int NAnum = 0;
REngine.SetEnvironmentVariables();
REngine MSS = REngine.GetInstance();
MSS.Initialize();
NumericMatrix Freq = MSS.CreateNumericMatrix(app.FreqMatrix);
MSS.SetSymbol("Freq", Freq);
NumericMatrix Count = MSS.CreateNumericMatrix(app.CountMatrix);
MSS.SetSymbol("Count", Count);
CharacterVector SampleName = MSS.CreateCharacterVector(app.SamName);
CharacterVector FeatureName = MSS.CreateCharacterVector(app.FeaName);
MSS.SetSymbol("FeatureName", FeatureName);
MSS.SetSymbol("SampleName", SampleName);
List <string> SampleNameFreq = new List <string>();
for (int i = 0; i < SampleNum; i++)
{
SampleNameFreq.Add(SampleName[i] + "Freq");
}
IntegerVector RFeaNum = MSS.CreateInteger(FeatureNum);
NumericVector Ralpha = MSS.CreateNumeric(double.Parse(this.textBox1.Text.ToString()));
MSS.SetSymbol("n", RFeaNum);
MSS.SetSymbol("alpha", Ralpha);
List <List <double> > Freqtemp = new List <List <double> >();
List <double> FreqSum = new List <double>();
MSS.Evaluate("leastnum = ceiling ( qnorm(alpha/2)^2 )");
double leastnum = MSS.Evaluate("leastnum").AsNumeric().First();
if (this.comboBox1.SelectedIndex == 0)
{
for (int i = 0; i < FeatureNum; i++)
{
pvalue.Add(100);
for (int j = 0; j < SampleNum - 1; j++)
{
for (int k = j + 1; k < SampleNum; k++)
{
double probtemp = (app.CountMatrix[i, j] + app.CountMatrix[i, k]) / (app.SampleTotal[j] + app.SampleTotal[k]);
double stattemp = (app.FreqMatrix[i, j] - app.FreqMatrix[i, k]) / Math.Sqrt(probtemp * (1 - probtemp) * (1 / app.SampleTotal[j] + 1 / app.SampleTotal[k]));
if (double.IsNaN(stattemp))
{
stattemp = 0;
}
NumericVector Rstat = MSS.CreateNumeric(stattemp);
MSS.SetSymbol("stat", Rstat);
MSS.Evaluate("p.value <- 2*(pnorm(-abs(stat)))");
double pvaluetemp;
if ((this.comboBox2.SelectedIndex == 1) && (app.CountMatrix[i, j] < leastnum) && (app.CountMatrix[i, k] < leastnum))
{
pvaluetemp = 100;
}
else
{
pvaluetemp = MSS.GetSymbol("p.value").AsNumeric().First();
}
if (pvaluetemp != 100)
{
pvalue[i] = Math.Min((double)pvalue[i], (double)pvaluetemp);
}
}
}
}
NumericVector Rpvalue = MSS.CreateNumericVector(pvalue);
MSS.SetSymbol("p.value", Rpvalue);
MSS.Evaluate("NAnum = length(p.value[p.value == 100])");
NAnum = Convert.ToInt32(MSS.GetSymbol("NAnum").AsNumeric().First());
MSS.Evaluate("p.value[p.value == 100] = NA");
MSS.Evaluate("bonferroni.p <- p.adjust(p.value,\"bonferroni\")");
MSS.Evaluate("bonferroni.p[which(bonferroni.p == NA)] = 100");
MSS.Evaluate("fdr.p <- p.adjust(p.value,\"fdr\")");
MSS.Evaluate("fdr.p[which(fdr.p == NA)] = 100");
for (int i = 0; i < FeatureNum; i++)
{
bonferroni[i] = MSS.GetSymbol("bonferroni.p").AsNumeric()[i];
fdr[i] = MSS.GetSymbol("fdr.p").AsNumeric()[i];
}
}
else if (this.comboBox1.SelectedIndex == 1)
{
for (int i = 0; i < FeatureNum; i++)
{
pvalue.Add(100);
}
for (int j = 0; j < SampleNum - 1; j++)
{
for (int k = 1; k < SampleNum; k++)
{
double Sum1 = 0;
double Sum2 = 0;
for (int i = 0; i < FeatureNum; i++)
{
Sum1 = Sum1 + app.CountMatrix[i, j];
Sum2 = Sum2 + app.CountMatrix[i, k];
}
for (int i = 0; i < FeatureNum; i++)
{
NumericVector n11 = MSS.CreateNumeric(app.CountMatrix[i, j]);
NumericVector n21 = MSS.CreateNumeric(app.CountMatrix[i, k]);
NumericVector n12 = MSS.CreateNumeric(Sum1 - app.CountMatrix[i, j]);
NumericVector n22 = MSS.CreateNumeric(Sum2 - app.CountMatrix[i, k]);
MSS.SetSymbol("n11", n11);
MSS.SetSymbol("n12", n12);
MSS.SetSymbol("n21", n21);
MSS.SetSymbol("n22", n22);
MSS.Evaluate("compare <- matrix(c(n11,n12,n21,n22),nr=2)");
MSS.Evaluate("p.value <- fisher.test(compare)$p.value");
double pvaluetemp = MSS.GetSymbol("p.value").AsNumeric().First();
pvalue[i] = Math.Min((double)pvalue[i], (double)pvaluetemp);
}
}
}
MSS.Evaluate("bonferroni.p <- p.adjust(p.value,\"bonferroni\")");
MSS.Evaluate("fdr.p <- p.adjust(p.value,\"fdr\")");
for (int i = 0; i < FeatureNum; i++)
{
bonferroni[i] = MSS.GetSymbol("bonferroni.p").AsNumeric()[i];
fdr[i] = MSS.GetSymbol("fdr.p").AsNumeric()[i];
}
}
List <string> Annotation = new List <string>();
if (this.checkBox1.Checked)
{
if (this.radioButton2.Checked)
{
string strConnCOG;
strConnCOG = "Provider=Microsoft.ACE.OLEDB.12.0;" + "Data Source=" + System.Windows.Forms.Application.StartupPath + "/COG.xlsx" + ";" + "Extended Properties=\"Excel 12.0;HDR=YES;IMEX=1\"";
OleDbConnection OleConnCOG = new OleDbConnection(strConnCOG);
OleConnCOG.Open();
String sqlCOG = "SELECT * FROM [Sheet1$]";
OleDbDataAdapter OleDaExcelCOG = new OleDbDataAdapter(sqlCOG, OleConnCOG);
app.OleDsExcleCOG = new DataSet();
OleDaExcelCOG.Fill(app.OleDsExcleCOG, "Sheet1");
OleConnCOG.Close();
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < app.OleDsExcleCOG.Tables[0].Rows.Count; j++)
{
if (string.Equals(FeatureName[i], app.OleDsExcleCOG.Tables[0].Rows[j][0].ToString()))
{
Annotation.Add(app.OleDsExcleCOG.Tables[0].Rows[j][1].ToString());
}
}
if (Annotation.Count < i + 1)
{
Annotation.Add("No Annotation!");
}
}
}
else if (this.radioButton1.Checked)
{
string strConnPFAM;
strConnPFAM = "Provider=Microsoft.ACE.OLEDB.12.0;" + "Data Source=" + System.Windows.Forms.Application.StartupPath + "/PFAM.xlsx" + ";" + "Extended Properties=\"Excel 12.0;HDR=YES;IMEX=1\"";
OleDbConnection OleConnPFAM = new OleDbConnection(strConnPFAM);
OleConnPFAM.Open();
String sqlPFAM = "SELECT * FROM [Sheet1$]";
OleDbDataAdapter OleDaExcelPFAM = new OleDbDataAdapter(sqlPFAM, OleConnPFAM);
app.OleDsExclePFAM = new DataSet();
OleDaExcelPFAM.Fill(app.OleDsExclePFAM, "Sheet1");
OleConnPFAM.Close();
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < app.OleDsExclePFAM.Tables[0].Rows.Count; j++)
{
if (string.Equals(FeatureName[i], app.OleDsExclePFAM.Tables[0].Rows[j][0].ToString()))
{
Annotation.Add(app.OleDsExclePFAM.Tables[0].Rows[j][1].ToString());
}
}
if (Annotation.Count < i + 1)
{
Annotation.Add("No Annotation!");
}
}
}
}
DataTable dt = new DataTable();
dt.Columns.Add("Feature", typeof(string));
for (int i = 0; i < SampleNum; i++)
{
dt.Columns.Add(app.SamName[i], typeof(double));
}
dt.Columns.Add("p.value", typeof(double));
dt.Columns.Add("bonferroni.p", typeof(double));
dt.Columns.Add("fdr.p", typeof(double));
dt.Columns.Add("Annotation", typeof(string));
for (int i = 0; i < SampleNum; i++)
{
dt.Columns.Add(SampleNameFreq[i], typeof(double));
}
for (int i = 0; i < FeatureNum; i++)
{
DataRow dr = dt.NewRow();
dr[0] = FeatureName[i];
for (int j = 1; j < SampleNum + 1; j++)
{
dr[j] = app.CountMatrix[i, j - 1];
}
if (pvalue[i] == 100)
{
dr[SampleNum + 1] = DBNull.Value;
dr[SampleNum + 2] = DBNull.Value;
dr[SampleNum + 3] = DBNull.Value;
}
else
{
dr[SampleNum + 1] = pvalue[i];
dr[SampleNum + 2] = bonferroni[i];
dr[SampleNum + 3] = fdr[i];
}
if (this.checkBox1.Checked)
{
dr[SampleNum + 4] = Annotation[i];
}
else
{
dr[SampleNum + 4] = null;
}
for (int j = 0; j < SampleNum; j++)
{
dr[j + SampleNum + 5] = app.FreqMatrix[i, j];
}
dt.Rows.Add(dr);
}
DataTable dtCopy = dt.Copy();
DataTable dttemp = dt.Copy();
dttemp.Clear();
DataView dv = dt.DefaultView;
dv.Sort = "p.value";
dtCopy = dv.ToTable();
for (int i = 0; i < NAnum; i++)
{
DataRow row = dtCopy.Rows[i];
dttemp.Rows.Add(row.ItemArray);
}
for (int i = 0; i < NAnum; i++)
{
dtCopy.Rows.RemoveAt(0);
}
dtCopy.Merge(dttemp);
Microsoft.Office.Interop.Excel.Application xlApp = new Microsoft.Office.Interop.Excel.Application();
System.Globalization.CultureInfo CurrentCI = System.Threading.Thread.CurrentThread.CurrentCulture;
System.Threading.Thread.CurrentThread.CurrentCulture = new System.Globalization.CultureInfo("en-US");
Microsoft.Office.Interop.Excel.Workbooks workbooks = xlApp.Workbooks;
Microsoft.Office.Interop.Excel.Workbook workbook = workbooks.Add(Microsoft.Office.Interop.Excel.XlWBATemplate.xlWBATWorksheet);
Microsoft.Office.Interop.Excel.Worksheet worksheet = (Microsoft.Office.Interop.Excel.Worksheet)workbook.Worksheets[1];
Microsoft.Office.Interop.Excel.Range range;
long totalCount = dtCopy.Rows.Count;
long rowRead = 0;
float percent = 0;
for (int i = 0; i < dtCopy.Columns.Count - SampleNum; i++)
{
worksheet.Cells[1, i + 1] = dtCopy.Columns[i].ColumnName;
range = (Microsoft.Office.Interop.Excel.Range)worksheet.Cells[1, i + 1];
range.Interior.ColorIndex = 15;
range.Font.Bold = true;
}
for (int r = 0; r < dtCopy.Rows.Count; r++)
{
for (int i = 0; i < dtCopy.Columns.Count - SampleNum; i++)
{
worksheet.Cells[r + 2, i + 1] = dtCopy.Rows[r][i].ToString();
}
rowRead++;
percent = ((float)(100 * rowRead)) / totalCount;
}
xlApp.Visible = true;
int pnum = 0;
for (int i = 0; i < FeatureNum; i++)
{
try
{
if (double.Parse(dtCopy.Rows[i][SampleNum].ToString()) < double.Parse(this.textBox1.Text.ToString()))
{
pnum++;
}
}
catch
{ }
}
double[,] df = new double[Math.Min(10, FeatureNum), SampleNum];
for (int i = 0; i < Math.Min(10, FeatureNum); i++)
{
for (int j = 0; j < SampleNum; j++)
{
df[i, j] = double.Parse(dtCopy.Rows[i][SampleNum + 5 + j].ToString());
}
}
if (this.checkBox2.Checked)
{
string[] rownamesdf = new string[Math.Min(10, FeatureNum)];
for (int i = 0; i < Math.Min(10, FeatureNum); i++)
{
rownamesdf[i] = dtCopy.Rows[i][0].ToString();
}
CharacterVector Rrownamesdf = MSS.CreateCharacterVector(rownamesdf);
MSS.SetSymbol("Rownamedf", Rrownamesdf);
NumericMatrix Rdf = MSS.CreateNumericMatrix(df);
MSS.SetSymbol("Freqdf", Rdf);
NumericVector RRow = MSS.CreateNumeric(Math.Min(10, FeatureNum));
MSS.SetSymbol("selrow", RRow);
MSS.Evaluate("Freqdf <- as.data.frame(Freqdf)");
MSS.Evaluate("rownames(Freqdf) <- Rownamedf");
MSS.Evaluate("colnames(Freqdf) <- SampleName");
MSS.Evaluate("colournum <- rainbow(dim(Freqdf)[2])");
MSS.Evaluate("plotdata <- t(Freqdf)");
MSS.Evaluate("windows()");
MSS.Evaluate("barplot(plotdata,main=\"features with top varition\",ylab=\"Freq\",beside=TRUE,horiz=FALSE, cex.names=0.6,col=colournum)");
MSS.Evaluate("legend(\"topright\",SampleName,fill=colournum)");
}
if (pnum > 0)
{
double[,] dfall = new double[pnum, SampleNum];
for (int i = 0; i < pnum; i++)
{
for (int j = 0; j < SampleNum; j++)
{
dfall[i, j] = double.Parse(dtCopy.Rows[i][SampleNum + 5 + j].ToString());
}
}
string[] rownamesall = new string[pnum];
for (int i = 0; i < pnum; i++)
{
rownamesall[i] = dtCopy.Rows[i][0].ToString();
}
CharacterVector Rrownamesall = MSS.CreateCharacterVector(rownamesall);
MSS.SetSymbol("Rownameall", Rrownamesall);
NumericMatrix Rdfall = MSS.CreateNumericMatrix(dfall);
MSS.SetSymbol("Freqdfall", Rdfall);
NumericVector RRowall = MSS.CreateNumeric(pnum);
MSS.SetSymbol("selrowall", RRowall);
MSS.Evaluate("Freqdfall <- as.data.frame(Freqdfall)");
MSS.Evaluate("rownames(Freqdfall) <- Rownameall");
MSS.Evaluate("colnames(Freqdfall) <- SampleName");
MSS.Evaluate("distance <- as.dist(1-abs(cor(Freqdfall)))");
if (this.checkBox3.Checked)
{
MSS.Evaluate("fit <- cmdscale(distance, eig=TRUE, k=2)");
MSS.Evaluate("x <- fit$points[,1]");
MSS.Evaluate("y <- fit$points[,2]");
MSS.Evaluate("minx <- min(x)");
MSS.Evaluate("miny <- min(y)");
MSS.Evaluate("maxx <- max(x)");
MSS.Evaluate("maxy <- max(y)");
MSS.Evaluate("randx <- maxx - minx");
MSS.Evaluate("randy <- maxy - miny");
MSS.Evaluate("llimx <- minx - randx/10");
MSS.Evaluate("hlimx <- maxx + randx/3");
MSS.Evaluate("llimy <- miny - randy/10");
MSS.Evaluate("hlimy <- maxy + randy/3");
MSS.Evaluate("windows()");
MSS.Evaluate("plot(x,y,xlab=\"Coordinate 1\",ylab=\"Coordinate 2\",main=\"MDS\", pch=c(0,1,2,5,6), col=rainbow(7), type=\"p\",xlim = c(llimx,hlimx), ylim = c(llimy,hlimy))");
if (this.comboBox3.SelectedIndex == 0)
{
MSS.Evaluate("legend(\"topright\",colnames(Freqdfall),pch=c(0,1,2,5,6),col=rainbow(7),cex = 0.8)");
}
else if (this.comboBox3.SelectedIndex == 1)
{
MSS.Evaluate("text(x,y,labels=SampleName,pos=4)");
}
}
if (this.checkBox4.Checked)
{
MSS.Evaluate("windows()");
MSS.Evaluate("plot(hclust(distance),main =\"Samples Clust\")");
}
}
else
{
MessageBox.Show("No differntially abundant features!!");
}
if (this.checkBox5.Checked)
{
int Rownum = 0;
for (int i = 0; i < FeatureNum; i++)
{
double tempSum = 0;
double tempMean = 0;
for (int j = 0; j < SampleNum; j++)
{
tempSum = tempSum + app.FreqMatrix[i, j];
}
tempMean = tempSum / (SampleNum);
if (tempSum > 0)
{
FreqSum.Add(tempSum);
List <double> tempRow = new List <double>();
for (int j = 0; j < SampleNum; j++)
{
tempRow.Add(app.FreqMatrix[i, j] / tempMean);
}
Freqtemp.Add(tempRow);
Rownum = Rownum + 1;
}
}
for (int i = 0; i < Rownum; i++)
{
for (int j = 0; j < SampleNum; j++)
{
Freqtemp[i][j] = Math.Log(Freqtemp[i][j], 2);
if (Freqtemp[i][j] > 1)
{
Freqtemp[i][j] = 1;
}
else if (Freqtemp[i][j] < -1)
{
Freqtemp[i][j] = -1;
}
}
}
double[,] dfhm = new double[Math.Min(500, Rownum), SampleNum];
for (int i = 0; i < Math.Min(500, Rownum); i++)
{
for (int j = 0; j < SampleNum; j++)
{
dfhm[i, j] = double.Parse(Freqtemp[i][j].ToString());
}
}
string[] rownameshm = new string[Math.Min(500, Rownum)];
for (int i = 0; i < Math.Min(500, Rownum); i++)
{
rownameshm[i] = dtCopy.Rows[i][0].ToString();
}
CharacterVector Rrownameshm = MSS.CreateCharacterVector(rownameshm);
MSS.SetSymbol("Rownamehm", Rrownameshm);
NumericMatrix Rdfhm = MSS.CreateNumericMatrix(dfhm);
MSS.SetSymbol("Freqdfhm", Rdfhm);
NumericVector RRowhm = MSS.CreateNumeric(Math.Min(500, Rownum));
MSS.SetSymbol("plotnum", RRowhm);
MSS.Evaluate("Freqdfhm <- as.data.frame(Freqdfhm)");
MSS.Evaluate("rownames(Freqdfhm) <- Rownamehm");
MSS.Evaluate("colnames(Freqdfhm) <- SampleName");
MSS.Evaluate("Freqdfhm <- as.matrix(Freqdfhm)");
MSS.Evaluate("library(pheatmap)");
MSS.Evaluate("windows()");
if (this.checkBox6.Checked)
{
if (this.checkBox7.Checked)
{
MSS.Evaluate("pheatmap(Freqdfhm[1:plotnum,],show_rownames=T,cluster_rows=T)");
}
else
{
MSS.Evaluate("pheatmap(Freqdfhm[1:plotnum,],show_rownames=F,cluster_rows=T)");
}
}
else
{
if (this.checkBox7.Checked)
{
MSS.Evaluate("pheatmap(Freqdfhm[1:plotnum,],show_rownames=T,cluster_rows=F)");
}
else
{
MSS.Evaluate("pheatmap(Freqdfhm[1:plotnum,],show_rownames=F,cluster_rows=F)");
}
}
}
this.Close();
}
private void button4_Click(object sender, EventArgs e)
{
int FeatureNum = app.FeaName.GetLength(0);
int SampleNum = app.SamName.GetLength(0);
List <double> prob = new List <double>();
List <double> stat = new List <double>();
List <double> pvalue = new List <double>();
double[] bonferroni = new double[FeatureNum];
double[] fdr = new double[FeatureNum];
int NAnum = 0;
if (SampleNum == 2)
{
REngine.SetEnvironmentVariables();
REngine TSS = REngine.GetInstance();
TSS.Initialize();
NumericMatrix Freq = TSS.CreateNumericMatrix(app.FreqMatrix);
TSS.SetSymbol("Freq", Freq);
NumericMatrix Count = TSS.CreateNumericMatrix(app.CountMatrix);
TSS.SetSymbol("Count", Count);
CharacterVector SampleName = TSS.CreateCharacterVector(app.SamName);
CharacterVector FeatureName = TSS.CreateCharacterVector(app.FeaName);
TSS.SetSymbol("FeatureName", FeatureName);
TSS.SetSymbol("SampleName", SampleName);
List <string> SampleNameFreq = new List <string>();
for (int i = 0; i < SampleNum; i++)
{
SampleNameFreq.Add(SampleName[i] + "Freq");
}
IntegerVector RFeaNum = TSS.CreateInteger(FeatureNum);
NumericVector Ralpha = TSS.CreateNumeric(double.Parse(this.textBox1.Text.ToString()));
TSS.SetSymbol("n", RFeaNum);
TSS.SetSymbol("alpha", Ralpha);
TSS.Evaluate("leastnum = ceiling ( qnorm(alpha/2)^2 )");
double leastnum = TSS.Evaluate("leastnum").AsNumeric().First();
if (this.comboBox1.SelectedIndex == 0)
{
for (int i = 0; i < FeatureNum; i++)
{
double temp = app.FreqMatrix[i, 0] - app.FreqMatrix[i, 1];
prob.Add(temp);
double P = (app.CountMatrix[i, 0] + app.CountMatrix[i, 1]) / (app.SampleTotal[0] + app.SampleTotal[1]);
double S = Math.Sqrt(P * (1 - P) * (1 / app.SampleTotal[0] + 1 / app.SampleTotal[1]));
double temp0 = prob[i] / S;
if (double.IsNaN(temp0))
{
temp0 = 0;
}
stat.Add(temp0);
}
for (int i = 0; i < FeatureNum; i++)
{
NumericVector Rstat = TSS.CreateNumeric(stat[i]);
TSS.SetSymbol("stat", Rstat);
TSS.Evaluate("p.value <- 2*(pnorm(-abs(stat)))");
if ((this.comboBox2.SelectedIndex == 1) && (app.CountMatrix[i, 0] < leastnum) && (app.CountMatrix[i, 1] < leastnum))
{
pvalue.Add(100);
}
else
{
pvalue.Add(TSS.GetSymbol("p.value").AsNumeric().First());
}
}
NumericVector Rpvalue = TSS.CreateNumericVector(pvalue);
TSS.SetSymbol("p.value", Rpvalue);
TSS.Evaluate("NAnum = length(p.value[p.value == 100])");
NAnum = Convert.ToInt32(TSS.GetSymbol("NAnum").AsNumeric().First());
TSS.Evaluate("p.value[p.value == 100] = NA");
TSS.Evaluate("bonferroni.p <- p.adjust(p.value,\"bonferroni\")");
TSS.Evaluate("bonferroni.p[which(bonferroni.p == NA)] = 100");
//double[] temp1 = (double[])hc1.GetSymbol("bonferroni.p");
TSS.Evaluate("fdr.p <- p.adjust(p.value,\"fdr\")");
TSS.Evaluate("fdr.p[which(fdr.p == NA)] = 100");
for (int i = 0; i < FeatureNum; i++)
{
bonferroni[i] = TSS.GetSymbol("bonferroni.p").AsNumeric()[i];
fdr[i] = TSS.GetSymbol("fdr.p").AsNumeric()[i];
}
}
else if (this.comboBox1.SelectedIndex == 1)
{
double Sum1 = 0;
double Sum2 = 0;
for (int i = 0; i < FeatureNum; i++)
{
Sum1 = Sum1 + app.CountMatrix[i, 0];
Sum2 = Sum2 + app.CountMatrix[i, 1];
}
for (int i = 0; i < FeatureNum; i++)
{
NumericVector n11 = TSS.CreateNumeric(app.CountMatrix[i, 0]);
NumericVector n21 = TSS.CreateNumeric(app.CountMatrix[i, 1]);
NumericVector n12 = TSS.CreateNumeric(Sum1 - app.CountMatrix[i, 0]);
NumericVector n22 = TSS.CreateNumeric(Sum2 - app.CountMatrix[i, 1]);
TSS.SetSymbol("n11", n11);
TSS.SetSymbol("n12", n12);
TSS.SetSymbol("n21", n21);
TSS.SetSymbol("n22", n22);
TSS.Evaluate("compare <- matrix(c(n11,n12,n21,n22),nr=2)");
TSS.Evaluate("p.value <- fisher.test(compare)$p.value");
pvalue.Add(TSS.GetSymbol("p.value").AsNumeric().First());
}
NumericVector Rpvalue = TSS.CreateNumericVector(pvalue);
TSS.SetSymbol("p.value", Rpvalue);
TSS.Evaluate("bonferroni.p <- p.adjust(p.value,\"bonferroni\")");
TSS.Evaluate("fdr.p <- p.adjust(p.value,\"fdr\")");
for (int i = 0; i < FeatureNum; i++)
{
bonferroni[i] = TSS.GetSymbol("bonferroni.p").AsNumeric()[i];
fdr[i] = TSS.GetSymbol("fdr.p").AsNumeric()[i];
}
}
List <string> Annotation = new List <string>();
if (this.checkBox1.Checked)
{
if (this.radioButton1.Checked)
{
string strConnCOG;
strConnCOG = "Provider=Microsoft.ACE.OLEDB.12.0;" + "Data Source=" + System.Windows.Forms.Application.StartupPath + "/COG.xlsx" + ";" + "Extended Properties=\"Excel 12.0;HDR=YES;IMEX=1\"";
OleDbConnection OleConnCOG = new OleDbConnection(strConnCOG);
OleConnCOG.Open();
String sqlCOG = "SELECT * FROM [Sheet1$]";
OleDbDataAdapter OleDaExcelCOG = new OleDbDataAdapter(sqlCOG, OleConnCOG);
app.OleDsExcleCOG = new DataSet();
OleDaExcelCOG.Fill(app.OleDsExcleCOG, "Sheet1");
OleConnCOG.Close();
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < app.OleDsExcleCOG.Tables[0].Rows.Count; j++)
{
if (string.Equals(FeatureName[i], app.OleDsExcleCOG.Tables[0].Rows[j][0].ToString()))
{
Annotation.Add(app.OleDsExcleCOG.Tables[0].Rows[j][1].ToString());
}
}
if (Annotation.Count < i + 1)
{
Annotation.Add("No Annotation!");
}
}
}
else if (this.radioButton2.Checked)
{
string strConnPFAM;
strConnPFAM = "Provider=Microsoft.ACE.OLEDB.12.0;" + "Data Source=" + System.Windows.Forms.Application.StartupPath + "/PFAM.xlsx" + ";" + "Extended Properties=\"Excel 12.0;HDR=YES;IMEX=1\"";
OleDbConnection OleConnPFAM = new OleDbConnection(strConnPFAM);
OleConnPFAM.Open();
String sqlPFAM = "SELECT * FROM [Sheet1$]";
OleDbDataAdapter OleDaExcelPFAM = new OleDbDataAdapter(sqlPFAM, OleConnPFAM);
app.OleDsExclePFAM = new DataSet();
OleDaExcelPFAM.Fill(app.OleDsExclePFAM, "Sheet1");
OleConnPFAM.Close();
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < app.OleDsExclePFAM.Tables[0].Rows.Count; j++)
{
if (string.Equals(FeatureName[i], app.OleDsExclePFAM.Tables[0].Rows[j][0].ToString()))
{
Annotation.Add(app.OleDsExclePFAM.Tables[0].Rows[j][1].ToString());
}
}
if (Annotation.Count < i + 1)
{
Annotation.Add("No Annotation!");
}
}
}
}
DataTable dt = new DataTable();
dt.Columns.Add("Feature", typeof(string));
for (int i = 0; i < SampleNum; i++)
{
dt.Columns.Add(app.SamName[i], typeof(double));
}
dt.Columns.Add("p.value", typeof(double));
dt.Columns.Add("bonferroni.p", typeof(double));
dt.Columns.Add("fdr.p", typeof(double));
dt.Columns.Add("Annotation", typeof(string));
for (int i = 0; i < SampleNum; i++)
{
dt.Columns.Add(SampleNameFreq[i], typeof(double));
}
for (int i = 0; i < FeatureNum; i++)
{
DataRow dr = dt.NewRow();
dr[0] = FeatureName[i];
for (int j = 1; j < SampleNum + 1; j++)
{
dr[j] = app.CountMatrix[i, j - 1];
}
if (pvalue[i] == 100)
{
dr[3] = DBNull.Value;
dr[4] = DBNull.Value;
dr[5] = DBNull.Value;
}
else
{
dr[3] = pvalue[i];
dr[4] = bonferroni[i];
dr[5] = fdr[i];
}
if (this.checkBox1.Checked)
{
dr[SampleNum + 4] = Annotation[i];
}
else
{
dr[SampleNum + 4] = null;
}
for (int j = 0; j < SampleNum; j++)
{
dr[j + SampleNum + 5] = app.FreqMatrix[i, j];
}
dt.Rows.Add(dr);
}
DataTable dtCopy = dt.Copy();
DataTable dttemp = dt.Copy();
dttemp.Clear();
DataView dv = dt.DefaultView;
dv.Sort = "p.value";
dtCopy = dv.ToTable();
for (int i = 0; i < NAnum; i++)
{
DataRow row = dtCopy.Rows[i];
dttemp.Rows.Add(row.ItemArray);
}
for (int i = 0; i < NAnum; i++)
{
dtCopy.Rows.RemoveAt(0);
}
Microsoft.Office.Interop.Excel.Application xlApp = new Microsoft.Office.Interop.Excel.Application();
System.Globalization.CultureInfo CurrentCI = System.Threading.Thread.CurrentThread.CurrentCulture;
System.Threading.Thread.CurrentThread.CurrentCulture = new System.Globalization.CultureInfo("en-US");
Microsoft.Office.Interop.Excel.Workbooks workbooks = xlApp.Workbooks;
Microsoft.Office.Interop.Excel.Workbook workbook = workbooks.Add(Microsoft.Office.Interop.Excel.XlWBATemplate.xlWBATWorksheet);
Microsoft.Office.Interop.Excel.Worksheet worksheet = (Microsoft.Office.Interop.Excel.Worksheet)workbook.Worksheets[1];
Microsoft.Office.Interop.Excel.Range range;
long totalCount = dtCopy.Rows.Count;
long rowRead = 0;
float percent = 0;
for (int i = 0; i < dtCopy.Columns.Count - SampleNum; i++)
{
worksheet.Cells[1, i + 1] = dtCopy.Columns[i].ColumnName;
range = (Microsoft.Office.Interop.Excel.Range)worksheet.Cells[1, i + 1];
range.Interior.ColorIndex = 15;
range.Font.Bold = true;
}
for (int r = 0; r < dtCopy.Rows.Count; r++)
{
for (int i = 0; i < dtCopy.Columns.Count - SampleNum; i++)
{
worksheet.Cells[r + 2, i + 1] = dtCopy.Rows[r][i].ToString();
}
rowRead++;
percent = ((float)(100 * rowRead)) / totalCount;
}
xlApp.Visible = true;
double[,] df = new double[Math.Min(10, FeatureNum), SampleNum];
for (int i = 0; i < Math.Min(10, FeatureNum); i++)
{
for (int j = 0; j < SampleNum; j++)
{
df[i, j] = double.Parse(dtCopy.Rows[i][SampleNum + 5 + j].ToString());
}
}
string[] rownames = new string[Math.Min(10, FeatureNum)];
for (int i = 0; i < Math.Min(10, FeatureNum); i++)
{
rownames[i] = dtCopy.Rows[i][0].ToString();
}
CharacterVector Rrownames = TSS.CreateCharacterVector(rownames);
TSS.SetSymbol("Rowname", Rrownames);
NumericMatrix Rdf = TSS.CreateNumericMatrix(df);
TSS.SetSymbol("Freqdf", Rdf);
NumericVector RRow = TSS.CreateNumeric(Math.Min(10, FeatureNum));
TSS.SetSymbol("selrow", RRow);
TSS.Evaluate("Freqdf <- as.data.frame(Freqdf)");
TSS.Evaluate("rownames(Freqdf) <- Rowname");
TSS.Evaluate("colnames(Freqdf) <- SampleName");
TSS.Evaluate("colournum <- rainbow(dim(Freqdf)[2])");
TSS.Evaluate("plotdata <- t(Freqdf)");
TSS.Evaluate("windows()");
TSS.Evaluate("barplot(plotdata,main=\"features with top varition\",ylab=\"Freq\",beside=TRUE,horiz=FALSE, cex.names=0.6,col=colournum)");
TSS.Evaluate("legend(\"topright\",SampleName,fill=colournum)");
}
else
{
MessageBox.Show("Sample number is more than two!!");
}
this.Close();
}
private void button4_Click(object sender, EventArgs e)
{
if (this.textBox3.Text == "")
{
MessageBox.Show("Please enter the sample number of Group I!", "WARNIMG");
Two_Groups_Ana TwoGroupsTest = new Two_Groups_Ana();
TwoGroupsTest.MdiParent = this.MdiParent;
TwoGroupsTest.Show();
this.Close();
}
else
{
int FeatureNum = app.FeaName.GetLength(0);
int SampleNum = app.SamName.GetLength(0);
List <double> prob = new List <double>();
List <double> stat = new List <double>();
List <double> pvalue = new List <double>();
double[] bonferroni = new double[FeatureNum];
double[] fdr = new double[FeatureNum];
int NAnum = 0;
REngine.SetEnvironmentVariables();
REngine TGS = REngine.GetInstance();
TGS.Initialize();
NumericMatrix Freq = TGS.CreateNumericMatrix(app.FreqMatrix);
TGS.SetSymbol("Freq", Freq);
NumericMatrix Count = TGS.CreateNumericMatrix(app.CountMatrix);
TGS.SetSymbol("Count", Count);
NumericVector RFeatureNum = TGS.CreateNumeric(FeatureNum);
NumericVector RSampleNum = TGS.CreateNumeric(SampleNum);
TGS.SetSymbol("FeatureNum", RFeatureNum);
TGS.SetSymbol("SampleNum", RSampleNum);
CharacterVector SampleName = TGS.CreateCharacterVector(app.SamName);
CharacterVector FeatureName = TGS.CreateCharacterVector(app.FeaName);
TGS.SetSymbol("FeatureName", FeatureName);
TGS.SetSymbol("SampleName", SampleName);
List <string> SampleNameFreq = new List <string>();
List <double?> OddRatio = new List <double?>();
List <double?> absOddRatio = new List <double?>();
List <List <double> > Freqtemp = new List <List <double> >();
List <double> FreqSum = new List <double>();
int Correct1 = 0;
int Correct2 = 0;
int method = 0;
int GroupNum = int.Parse(this.textBox3.Text.ToString());
NumericVector RGroupNum = TGS.CreateNumeric(GroupNum);
TGS.SetSymbol("Groupsep", RGroupNum);
for (int i = 0; i < SampleNum; i++)
{
SampleNameFreq.Add(SampleName[i] + "Freq");
}
if (this.comboBox1.SelectedIndex == 0)
{
int effNum1, effNum2;
TGS.Evaluate("FeatureSums1 <- rowSums(Count[,1:Groupsep])");
TGS.Evaluate("FeatureSums2 <- rowSums(Count[,Groupsep:SampleNum])");
TGS.Evaluate("effnum1 <- length(FeatureSums1[FeatureSums1 > Groupsep])");
TGS.Evaluate("effnum2 <- length(FeatureSums2[FeatureSums2 > (SampleNum - Groupsep)])");
effNum1 = Convert.ToInt32(TGS.GetSymbol("effnum1").AsNumeric().First());
effNum2 = Convert.ToInt32(TGS.GetSymbol("effnum2").AsNumeric().First());
for (int i = 0; i < FeatureNum; i++)
{
double rowsums1 = 0;
double rowsums2 = 0;
double[] rowsCount1 = new double[GroupNum];
for (int j = 0; j < GroupNum; j++)
{
rowsums1 = rowsums1 + app.CountMatrix[i, j];
rowsCount1[j] = app.CountMatrix[i, j];
}
if (rowsums1 > GroupNum)
{
NumericVector rowscount1 = TGS.CreateNumericVector(rowsCount1);
TGS.SetSymbol("rowcount1", rowscount1);
TGS.Evaluate("result1 <- ks.test(rowcount1,\"pnorm\",mean(rowcount1),sd(rowcount1))");
TGS.Evaluate("factor1 <- result1$p");
double prows1 = TGS.GetSymbol("factor1").AsNumeric().First();
if (prows1 < 0.05)
{
Correct1 = Correct1 + 1;
}
}
double[] rowsCount2 = new double[SampleNum - GroupNum];
for (int j = GroupNum; j < SampleNum; j++)
{
rowsums2 = rowsums2 + app.CountMatrix[i, j];
rowsCount2[j - GroupNum] = app.CountMatrix[i, j];
}
if (rowsums2 > (SampleNum - GroupNum))
{
NumericVector rowscount2 = TGS.CreateNumericVector(rowsCount2);
TGS.SetSymbol("rowcount2", rowscount2);
TGS.Evaluate("result2 <- ks.test(rowcount2,\"pnorm\",mean(rowcount2),sd(rowcount2))");
TGS.Evaluate("factor2 <- result2$p");
double prows2 = TGS.GetSymbol("factor2").AsNumeric().First();
if (prows2 < 0.05)
{
Correct2 = Correct2 + 1;
}
}
}
bool condition1 = (Correct1 >= effNum1 * 0.5) && (Correct2 >= effNum2 * 0.5);
bool condition2 = GroupNum == SampleNum - GroupNum;
if (condition1)
{
if (condition2)
{
method = 2;
}
else
{
method = 1;
}
}
else
{
if (condition2)
{
method = 4;
}
else
{
method = 3;
}
}
switch (method)
{
case 1:
MessageBox.Show("Statistical Method : t-test");
break;
case 2:
MessageBox.Show("Statistical Method : Pair t-test");
break;
case 3:
MessageBox.Show("Statistical Method : Mann-Whitney U test");
break;
case 4:
MessageBox.Show("Statistical Method : Wilcoxon sign-rank test");
break;
default:
break;
}
}
TGS.Evaluate("FreqMatrix <- as.data.frame(Freq)");
TGS.Evaluate("names(FreqMatrix) <- SampleName");
TGS.Evaluate("samp1_mean <- apply(FreqMatrix[,1:Groupsep],1,mean)");
TGS.Evaluate("samp2_mean <- apply(FreqMatrix[,(Groupsep+1):SampleNum],1,mean)");
TGS.Evaluate("samp1_sd <- apply(FreqMatrix[,1:Groupsep],1,sd)");
TGS.Evaluate("samp2_sd <- apply(FreqMatrix[,(Groupsep+1):SampleNum],1,sd)");
TGS.Evaluate("samp1_stat <- paste(samp1_mean,samp1_sd,sep=\"±\")");
TGS.Evaluate("samp2_stat <- paste(samp2_mean,samp2_sd,sep=\"±\")");
string[] s1_stat = (string[])TGS.GetSymbol("samp1_stat").AsCharacter().ToArray();
string[] s2_stat = (string[])TGS.GetSymbol("samp2_stat").AsCharacter().ToArray();
if (this.comboBox1.SelectedIndex != 6)
{
switch (this.comboBox1.SelectedIndex + method)
{
case 1:
for (int i = 1; i <= FeatureNum; i++)
{
TGS.SetSymbol("i", TGS.CreateNumeric(i));
TGS.Evaluate("group1_freq <- as.numeric(FreqMatrix[i,1:Groupsep])");
TGS.Evaluate("group2_freq <- as.numeric(FreqMatrix[i,(Groupsep+1):SampleNum])");
TGS.Evaluate("p.value <- t.test(group1_freq,group2_freq, paired=FALSE)$p.value");
pvalue.Add(TGS.GetSymbol("p.value").AsNumeric().First());
}
break;
case 2:
if (GroupNum != SampleNum - GroupNum)
{
MessageBox.Show("This statistical test must have same number samples in each category!", "WARNIMG");
break;
}
else
{
for (int i = 1; i <= FeatureNum; i++)
{
TGS.SetSymbol("i", TGS.CreateNumeric(i));
TGS.Evaluate("group1_freq <- as.numeric(FreqMatrix[i,1:Groupsep])");
TGS.Evaluate("group2_freq <- as.numeric(FreqMatrix[i,(Groupsep+1):SampleNum])");
TGS.Evaluate("p.value <- t.test(group1_freq,group2_freq, paired=TRUE)$p.value");
pvalue.Add(TGS.GetSymbol("p.value").AsNumeric().First());
}
break;
}
case 3:
for (int i = 1; i <= FeatureNum; i++)
{
TGS.SetSymbol("i", TGS.CreateNumeric(i));
TGS.Evaluate("group1_freq <- as.numeric(FreqMatrix[i,1:Groupsep])");
TGS.Evaluate("group2_freq <- as.numeric(FreqMatrix[i,(Groupsep+1):SampleNum])");
TGS.Evaluate("p.value <- wilcox.test(group1_freq,group2_freq,exact = FALSE)$p.value");
pvalue.Add(TGS.GetSymbol("p.value").AsNumeric().First());
}
break;
case 4:
if (GroupNum != SampleNum - GroupNum)
{
MessageBox.Show("This statistical test must have same number samples in each category!", "WARNIMG");
break;
}
else
{
for (int i = 1; i <= FeatureNum; i++)
{
TGS.SetSymbol("i", TGS.CreateNumeric(i));
TGS.Evaluate("group1_freq <- as.numeric(FreqMatrix[i,1:Groupsep])");
TGS.Evaluate("group2_freq <- as.numeric(FreqMatrix[i,(Groupsep+1):SampleNum])");
TGS.Evaluate("p.value <- wilcox.test(group1_freq,group2_freq,paired=TRUE,exact = FALSE)$p.value");
pvalue.Add(TGS.GetSymbol("p.value").AsNumeric().First());
}
break;
}
case 5:
double Sum1 = 0;
double Sum2 = 0;
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < GroupNum; j++)
{
Sum1 = Sum1 + app.CountMatrix[i, j];
}
for (int j = GroupNum; j < SampleNum; j++)
{
Sum2 = Sum2 + app.CountMatrix[i, j];
}
}
for (int i = 0; i < FeatureNum; i++)
{
double n11 = 0;
double n12 = 0;
double n21 = 0;
double n22 = 0;
for (int j = 0; j < GroupNum; j++)
{
n11 = n11 + app.CountMatrix[i, j];
}
for (int j = GroupNum; j < SampleNum; j++)
{
n21 = n21 + app.CountMatrix[i, j];
}
n12 = Sum1 - n11;
n22 = Sum2 - n21;
NumericVector Rn11 = TGS.CreateNumeric(n11);
NumericVector Rn21 = TGS.CreateNumeric(n21);
NumericVector Rn12 = TGS.CreateNumeric(n12);
NumericVector Rn22 = TGS.CreateNumeric(n22);
TGS.SetSymbol("n11", Rn11);
TGS.SetSymbol("n12", Rn12);
TGS.SetSymbol("n21", Rn21);
TGS.SetSymbol("n22", Rn22);
TGS.Evaluate("compare <- matrix(c(n11,n12,n21,n22),nr=2)");
TGS.Evaluate("p.value <- fisher.test(compare)$p.value");
pvalue.Add(TGS.GetSymbol("p.value").AsNumeric().First());
}
break;
default:
break;
}
NumericVector Rpvalue = TGS.CreateNumericVector(pvalue);
TGS.SetSymbol("p.value", Rpvalue);
TGS.Evaluate("NAnum = length(p.value[is.nan(p.value)])");
NAnum = Convert.ToInt32(TGS.GetSymbol("NAnum").AsNumeric().First());
TGS.Evaluate("bonferroni.p <- p.adjust(p.value,\"bonferroni\")");
TGS.Evaluate("fdr.p <- p.adjust(p.value,\"fdr\")");
for (int i = 0; i < FeatureNum; i++)
{
bonferroni[i] = TGS.GetSymbol("bonferroni.p").AsNumeric()[i];
fdr[i] = TGS.GetSymbol("fdr.p").AsNumeric()[i];
}
List <string> Annotation = new List <string>();
if (this.checkBox1.Checked)
{
if (this.radioButton1.Checked)
{
string strConnCOG;
strConnCOG = "Provider=Microsoft.ACE.OLEDB.12.0;" + "Data Source=" + System.Windows.Forms.Application.StartupPath + "/COG.xlsx" + ";" + "Extended Properties=\"Excel 12.0;HDR=YES;IMEX=1\"";
OleDbConnection OleConnCOG = new OleDbConnection(strConnCOG);
OleConnCOG.Open();
String sqlCOG = "SELECT * FROM [Sheet1$]";
OleDbDataAdapter OleDaExcelCOG = new OleDbDataAdapter(sqlCOG, OleConnCOG);
app.OleDsExcleCOG = new DataSet();
OleDaExcelCOG.Fill(app.OleDsExcleCOG, "Sheet1");
OleConnCOG.Close();
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < app.OleDsExcleCOG.Tables[0].Rows.Count; j++)
{
if (string.Equals(FeatureName[i], app.OleDsExcleCOG.Tables[0].Rows[j][0].ToString()))
{
Annotation.Add(app.OleDsExcleCOG.Tables[0].Rows[j][1].ToString());
}
}
if (Annotation.Count < i + 1)
{
Annotation.Add("No Annotation!");
}
}
}
else if (this.radioButton2.Checked)
{
string strConnPFAM;
strConnPFAM = "Provider=Microsoft.ACE.OLEDB.12.0;" + "Data Source=" + System.Windows.Forms.Application.StartupPath + "/PFAM.xlsx" + ";" + "Extended Properties=\"Excel 12.0;HDR=YES;IMEX=1\"";
OleDbConnection OleConnPFAM = new OleDbConnection(strConnPFAM);
OleConnPFAM.Open();
String sqlPFAM = "SELECT * FROM [Sheet1$]";
OleDbDataAdapter OleDaExcelPFAM = new OleDbDataAdapter(sqlPFAM, OleConnPFAM);
app.OleDsExclePFAM = new DataSet();
OleDaExcelPFAM.Fill(app.OleDsExclePFAM, "Sheet1");
OleConnPFAM.Close();
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < app.OleDsExclePFAM.Tables[0].Rows.Count; j++)
{
if (string.Equals(FeatureName[i], app.OleDsExclePFAM.Tables[0].Rows[j][0].ToString()))
{
Annotation.Add(app.OleDsExclePFAM.Tables[0].Rows[j][1].ToString());
}
}
if (Annotation.Count < i + 1)
{
Annotation.Add("No Annotation!");
}
}
}
}
DataTable dt = new DataTable();
dt.Columns.Add("Feature", typeof(string));
for (int i = 0; i < SampleNum; i++)
{
dt.Columns.Add(SampleName[i], typeof(double));;
}
dt.Columns.Add("group1", typeof(string));
dt.Columns.Add("group2", typeof(string));
dt.Columns.Add("p.value", typeof(double));
dt.Columns.Add("bonferroni.p", typeof(double));
dt.Columns.Add("fdr.p", typeof(double));
dt.Columns.Add("Annotation", typeof(string));
for (int i = 0; i < SampleNum; i++)
{
dt.Columns.Add(SampleNameFreq[i], typeof(double));
}
for (int i = 0; i < FeatureNum; i++)
{
DataRow dr = dt.NewRow();
dr[0] = FeatureName[i];
for (int j = 1; j <= SampleNum; j++)
{
dr[j] = app.CountMatrix[i, j - 1];
}
dr[SampleNum + 1] = s1_stat[i];
dr[SampleNum + 2] = s2_stat[i];
if (double.IsNaN(pvalue[i]))
{
dr[SampleNum + 3] = DBNull.Value;
dr[SampleNum + 4] = DBNull.Value;
dr[SampleNum + 5] = DBNull.Value;
}
else
{
dr[SampleNum + 3] = pvalue[i];
dr[SampleNum + 4] = bonferroni[i];
dr[SampleNum + 5] = fdr[i];
}
if (this.checkBox1.Checked)
{
dr[SampleNum + 6] = Annotation[i];
}
else
{
dr[SampleNum + 6] = null;
}
for (int j = 0; j < SampleNum; j++)
{
dr[j + SampleNum + 7] = app.FreqMatrix[i, j];
}
dt.Rows.Add(dr);
}
DataTable dtCopy = dt.Copy();
DataTable dttemp = dt.Copy();
dttemp.Clear();
DataView dv = dt.DefaultView;
dv.Sort = "p.value";
dtCopy = dv.ToTable();
for (int i = 0; i < NAnum; i++)
{
DataRow row = dtCopy.Rows[i];
dttemp.Rows.Add(row.ItemArray);
}
for (int i = 0; i < NAnum; i++)
{
dtCopy.Rows.RemoveAt(0);
}
Microsoft.Office.Interop.Excel.Application xlApp = new Microsoft.Office.Interop.Excel.Application();
System.Globalization.CultureInfo CurrentCI = System.Threading.Thread.CurrentThread.CurrentCulture;
System.Threading.Thread.CurrentThread.CurrentCulture = new System.Globalization.CultureInfo("en-US");
Microsoft.Office.Interop.Excel.Workbooks workbooks = xlApp.Workbooks;
Microsoft.Office.Interop.Excel.Workbook workbook = workbooks.Add(Microsoft.Office.Interop.Excel.XlWBATemplate.xlWBATWorksheet);
Microsoft.Office.Interop.Excel.Worksheet worksheet = (Microsoft.Office.Interop.Excel.Worksheet)workbook.Worksheets[1];
Microsoft.Office.Interop.Excel.Range range;
long totalCount = dtCopy.Rows.Count;
long rowRead = 0;
float percent = 0;
for (int i = 0; i < dtCopy.Columns.Count - SampleNum; i++)
{
worksheet.Cells[1, i + 1] = dtCopy.Columns[i].ColumnName;
range = (Microsoft.Office.Interop.Excel.Range)worksheet.Cells[1, i + 1];
range.Interior.ColorIndex = 15;
range.Font.Bold = true;
}
for (int r = 0; r < dtCopy.Rows.Count; r++)
{
for (int i = 0; i < dtCopy.Columns.Count - SampleNum; i++)
{
worksheet.Cells[r + 2, i + 1] = dtCopy.Rows[r][i].ToString();
}
rowRead++;
percent = ((float)(100 * rowRead)) / totalCount;
}
xlApp.Visible = true;
int pnum = 0;
for (int i = 0; i < FeatureNum; i++)
{
try
{
if (double.Parse(dtCopy.Rows[i][SampleNum + 3].ToString()) < double.Parse(this.textBox1.Text.ToString()))
{
pnum++;
}
}
catch
{ }
}
double[,] df = new double[Math.Min(10, FeatureNum), SampleNum];
for (int i = 0; i < Math.Min(10, FeatureNum); i++)
{
for (int j = 0; j < SampleNum; j++)
{
df[i, j] = double.Parse(dtCopy.Rows[i][SampleNum + 7 + j].ToString());
}
}
if (this.checkBox2.Checked)
{
string[] rownamesdf = new string[Math.Min(10, FeatureNum)];
for (int i = 0; i < Math.Min(10, FeatureNum); i++)
{
rownamesdf[i] = dtCopy.Rows[i][0].ToString();
}
CharacterVector Rrownamesdf = TGS.CreateCharacterVector(rownamesdf);
TGS.SetSymbol("Rownamedf", Rrownamesdf);
NumericMatrix Rdf = TGS.CreateNumericMatrix(df);
TGS.SetSymbol("Freqdf", Rdf);
NumericVector RRow = TGS.CreateNumeric(Math.Min(10, FeatureNum));
TGS.SetSymbol("selrow", RRow);
TGS.Evaluate("Freqdf <- as.data.frame(Freqdf)");
TGS.Evaluate("rownames(Freqdf) <- Rownamedf");
TGS.Evaluate("colnames(Freqdf) <- SampleName");
TGS.Evaluate("colournum <- rainbow(dim(Freqdf)[2])");
TGS.Evaluate("plotdata <- t(Freqdf)");
TGS.Evaluate("windows()");
TGS.Evaluate("barplot(plotdata,main=\"features with top varition\",ylab=\"Freq\",beside=TRUE,horiz=FALSE, cex.names=0.6,col=colournum)");
TGS.Evaluate("legend(\"topright\",SampleName,fill=colournum)");
}
if (pnum > 0)
{
double[,] dfall = new double[pnum, SampleNum];
for (int i = 0; i < pnum; i++)
{
for (int j = 0; j < SampleNum; j++)
{
dfall[i, j] = double.Parse(dtCopy.Rows[i][SampleNum + 7 + j].ToString());
}
}
string[] rownamesall = new string[pnum];
for (int i = 0; i < pnum; i++)
{
rownamesall[i] = dtCopy.Rows[i][0].ToString();
}
CharacterVector Rrownamesall = TGS.CreateCharacterVector(rownamesall);
TGS.SetSymbol("Rownameall", Rrownamesall);
NumericMatrix Rdfall = TGS.CreateNumericMatrix(dfall);
TGS.SetSymbol("Freqdfall", Rdfall);
NumericVector RRowall = TGS.CreateNumeric(pnum);
TGS.SetSymbol("selrowall", RRowall);
TGS.Evaluate("Freqdfall <- as.data.frame(Freqdfall)");
TGS.Evaluate("rownames(Freqdfall) <- Rownameall");
TGS.Evaluate("colnames(Freqdfall) <- SampleName");
TGS.Evaluate("distance <- as.dist(1-abs(cor(Freqdfall)))");
if (this.checkBox3.Checked)
{
TGS.Evaluate("fit <- cmdscale(distance, eig=TRUE, k=2)");
TGS.Evaluate("x <- fit$points[,1]");
TGS.Evaluate("y <- fit$points[,2]");
TGS.Evaluate("minx <- min(x)");
TGS.Evaluate("miny <- min(y)");
TGS.Evaluate("maxx <- max(x)");
TGS.Evaluate("maxy <- max(y)");
TGS.Evaluate("randx <- maxx - minx");
TGS.Evaluate("randy <- maxy - miny");
TGS.Evaluate("llimx <- minx - randx/10");
TGS.Evaluate("hlimx <- maxx + randx/3");
TGS.Evaluate("llimy <- miny - randy/10");
TGS.Evaluate("hlimy <- maxy + randy/3");
TGS.Evaluate("windows()");
TGS.Evaluate("plot(x,y,xlab=\"Coordinate 1\",ylab=\"Coordinate 2\",main=\"MDS\", pch=c(rep(0,Groupsep),rep(1,(length(SampleName)-Groupsep))),col=c(rep(\"red\",Groupsep),rep(\"green\",(length(SampleName)-Groupsep))), type=\"p\",xlim = c(llimx,hlimx), ylim = c(llimy,hlimy))");
if (this.comboBox3.SelectedIndex == 0)
{
TGS.Evaluate("legend(\"topright\",colnames(Freqdfall),pch=c(rep(0,Groupsep),rep(1,(length(SampleName)-Groupsep))),col=c(rep(\"red\",Groupsep),rep(\"green\",(length(SampleName)-Groupsep))),cex = 0.8)");
}
else if (this.comboBox3.SelectedIndex == 1)
{
TGS.Evaluate("text(x,y,labels=SampleName,pos=4)");
}
}
if (this.checkBox4.Checked)
{
TGS.Evaluate("windows()");
TGS.Evaluate("plot(hclust(distance),main =\"Samples Clust\")");
}
}
else
{
MessageBox.Show("No differntially abundant features!!");
}
if (this.checkBox5.Checked)
{
int Rownum = 0;
for (int i = 0; i < FeatureNum; i++)
{
double tempSum = 0;
double tempMean = 0;
for (int j = 0; j < SampleNum; j++)
{
tempSum = tempSum + app.FreqMatrix[i, j];
}
tempMean = tempSum / (SampleNum);
if (tempSum > 0)
{
FreqSum.Add(tempSum);
List <double> tempRow = new List <double>();
for (int j = 0; j < SampleNum; j++)
{
tempRow.Add(app.FreqMatrix[i, j] / tempMean);
}
Freqtemp.Add(tempRow);
Rownum = Rownum + 1;
}
}
for (int i = 0; i < Rownum; i++)
{
for (int j = 0; j < SampleNum; j++)
{
Freqtemp[i][j] = Math.Log(Freqtemp[i][j], 2);
if (Freqtemp[i][j] > 1)
{
Freqtemp[i][j] = 1;
}
else if (Freqtemp[i][j] < -1)
{
Freqtemp[i][j] = -1;
}
}
}
double[,] dfhm = new double[Math.Min(500, Rownum), SampleNum];
for (int i = 0; i < Math.Min(500, Rownum); i++)
{
for (int j = 0; j < SampleNum; j++)
{
dfhm[i, j] = double.Parse(Freqtemp[i][j].ToString());
}
}
string[] rownameshm = new string[Math.Min(500, Rownum)];
for (int i = 0; i < Math.Min(500, Rownum); i++)
{
rownameshm[i] = dtCopy.Rows[i][0].ToString();
}
CharacterVector Rrownameshm = TGS.CreateCharacterVector(rownameshm);
TGS.SetSymbol("Rownamehm", Rrownameshm);
NumericMatrix Rdfhm = TGS.CreateNumericMatrix(dfhm);
TGS.SetSymbol("Freqdfhm", Rdfhm);
NumericVector RRowhm = TGS.CreateNumeric(Math.Min(500, Rownum));
TGS.SetSymbol("plotnum", RRowhm);
TGS.Evaluate("Freqdfhm <- as.data.frame(Freqdfhm)");
TGS.Evaluate("rownames(Freqdfhm) <- Rownamehm");
TGS.Evaluate("colnames(Freqdfhm) <- SampleName");
TGS.Evaluate("Freqdfhm <- as.matrix(Freqdfhm)");
TGS.Evaluate("library(pheatmap)");
TGS.Evaluate("windows()");
if (this.checkBox6.Checked)
{
if (this.checkBox7.Checked)
{
TGS.Evaluate("pheatmap(Freqdfhm[1:plotnum,],show_rownames=T,cluster_rows=T)");
}
else
{
TGS.Evaluate("pheatmap(Freqdfhm[1:plotnum,],show_rownames=F,cluster_rows=T)");
}
}
else
{
if (this.checkBox7.Checked)
{
TGS.Evaluate("pheatmap(Freqdfhm[1:plotnum,],show_rownames=T,cluster_rows=F)");
}
else
{
TGS.Evaluate("pheatmap(Freqdfhm[1:plotnum,],show_rownames=F,cluster_rows=F)");
}
}
}
}
else if (this.comboBox1.SelectedIndex == 6)
{
double Sum1 = 0;
double Sum2 = 0;
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < GroupNum; j++)
{
Sum1 = Sum1 + app.CountMatrix[i, j];
}
for (int j = GroupNum; j < SampleNum - 1; j++)
{
Sum2 = Sum2 + app.CountMatrix[i, j];
}
}
TGS.SetSymbol("Sum1", TGS.CreateNumeric(Sum1));
TGS.SetSymbol("Sum2", TGS.CreateNumeric(Sum2));
TGS.Evaluate("R <- Sum1/Sum2");
TGS.Evaluate("treatadd <- R/(R+1)");
TGS.Evaluate("controladd <- 1/(R+1)");
for (int i = 0; i < FeatureNum; i++)
{
double n11 = 0;
double n12 = 0;
double n21 = 0;
double n22 = 0;
for (int j = 0; j < GroupNum; j++)
{
n11 = n11 + app.Count[i][j];
}
for (int j = GroupNum; j < SampleNum - 1; j++)
{
n21 = n21 + app.Count[i][j];
}
if ((n11 < GroupNum) && (n21 < SampleNum - 1 - GroupNum))
{
OddRatio.Add(null);
absOddRatio.Add(null);
}
else
{
n12 = Sum1 - n11;
n22 = Sum2 - n21;
TGS.SetSymbol("n11", TGS.CreateNumeric(n11));
TGS.SetSymbol("n12", TGS.CreateNumeric(n12));
TGS.SetSymbol("n21", TGS.CreateNumeric(n21));
TGS.SetSymbol("n22", TGS.CreateNumeric(n22));
TGS.Evaluate("odd_ratio <- log2(((n11+treatadd)*(n22+controladd))/((n21+controladd)*(n12+treatadd )))");
OddRatio.Add(double.Parse(TGS.GetSymbol("odd_ratio").ToString()));
absOddRatio.Add(Math.Abs(double.Parse(TGS.GetSymbol("odd_ratio").ToString())));
}
}
List <string> Annotation = new List <string>();
if (this.checkBox1.Checked)
{
if (this.radioButton1.Checked)
{
string strConnCOG;
strConnCOG = "Provider=Microsoft.ACE.OLEDB.12.0;" + "Data Source=" + System.Windows.Forms.Application.StartupPath + "/COG.xlsx" + ";" + "Extended Properties=\"Excel 12.0;HDR=YES;IMEX=1\"";
OleDbConnection OleConnCOG = new OleDbConnection(strConnCOG);
OleConnCOG.Open();
String sqlCOG = "SELECT * FROM [Sheet1$]";
OleDbDataAdapter OleDaExcelCOG = new OleDbDataAdapter(sqlCOG, OleConnCOG);
app.OleDsExcleCOG = new DataSet();
OleDaExcelCOG.Fill(app.OleDsExcleCOG, "Sheet1");
OleConnCOG.Close();
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < app.OleDsExcleCOG.Tables[0].Rows.Count; j++)
{
if (string.Equals(FeatureName[i], app.OleDsExcleCOG.Tables[0].Rows[j][0].ToString()))
{
Annotation.Add(app.OleDsExcleCOG.Tables[0].Rows[j][1].ToString());
}
}
if (Annotation.Count < i + 1)
{
Annotation.Add("No Annotation!");
}
}
}
else if (this.radioButton2.Checked)
{
string strConnPFAM;
strConnPFAM = "Provider=Microsoft.ACE.OLEDB.12.0;" + "Data Source=" + System.Windows.Forms.Application.StartupPath + "/PFAM.xlsx" + ";" + "Extended Properties=\"Excel 12.0;HDR=YES;IMEX=1\"";
OleDbConnection OleConnPFAM = new OleDbConnection(strConnPFAM);
OleConnPFAM.Open();
String sqlPFAM = "SELECT * FROM [Sheet1$]";
OleDbDataAdapter OleDaExcelPFAM = new OleDbDataAdapter(sqlPFAM, OleConnPFAM);
app.OleDsExclePFAM = new DataSet();
OleDaExcelPFAM.Fill(app.OleDsExclePFAM, "Sheet1");
OleConnPFAM.Close();
for (int i = 0; i < FeatureNum; i++)
{
for (int j = 0; j < app.OleDsExclePFAM.Tables[0].Rows.Count; j++)
{
if (string.Equals(FeatureName[i], app.OleDsExclePFAM.Tables[0].Rows[j][0].ToString()))
{
Annotation.Add(app.OleDsExclePFAM.Tables[0].Rows[j][1].ToString());
}
}
if (Annotation.Count < i + 1)
{
Annotation.Add("No Annotation!");
}
}
}
}
DataTable dt = new DataTable();
dt.Columns.Add("Feature", typeof(string));
for (int i = 0; i < SampleNum; i++)
{
dt.Columns.Add(SampleName[i], typeof(double));;
}
dt.Columns.Add("Odd_Ratio", typeof(double));
dt.Columns.Add("abs_Odd_Ratio", typeof(double));
dt.Columns.Add("Annotation", typeof(string));
for (int i = 0; i < FeatureNum; i++)
{
DataRow dr = dt.NewRow();
dr[0] = FeatureName[i];
for (int j = 1; j <= SampleNum; j++)
{
dr[j] = app.CountMatrix[i, j - 1];
}
if (OddRatio[i] == null)
{
dr[SampleNum] = DBNull.Value;
dr[SampleNum + 1] = DBNull.Value;
}
else
{
dr[SampleNum] = OddRatio[i];
dr[SampleNum + 1] = absOddRatio[i];
}
if (this.checkBox1.Checked)
{
dr[SampleNum + 2] = Annotation[i];
}
else
{
dr[SampleNum + 2] = null;
}
dt.Rows.Add(dr);
}
DataTable dtCopy = dt.Copy();
DataView dv = dt.DefaultView;
dv.Sort = "abs_Odd_Ratio DESC";
dtCopy = dv.ToTable();
Microsoft.Office.Interop.Excel.Application xlApp = new Microsoft.Office.Interop.Excel.Application();
System.Globalization.CultureInfo CurrentCI = System.Threading.Thread.CurrentThread.CurrentCulture;
System.Threading.Thread.CurrentThread.CurrentCulture = new System.Globalization.CultureInfo("en-US");
Microsoft.Office.Interop.Excel.Workbooks workbooks = xlApp.Workbooks;
Microsoft.Office.Interop.Excel.Workbook workbook = workbooks.Add(Microsoft.Office.Interop.Excel.XlWBATemplate.xlWBATWorksheet);
Microsoft.Office.Interop.Excel.Worksheet worksheet = (Microsoft.Office.Interop.Excel.Worksheet)workbook.Worksheets[1];
Microsoft.Office.Interop.Excel.Range range;
long totalCount = dtCopy.Rows.Count;
long rowRead = 0;
float percent = 0;
for (int i = 0; i < dtCopy.Columns.Count; i++)
{
worksheet.Cells[1, i + 1] = dtCopy.Columns[i].ColumnName;
range = (Microsoft.Office.Interop.Excel.Range)worksheet.Cells[1, i + 1];
range.Interior.ColorIndex = 15;
range.Font.Bold = true;
}
for (int r = 0; r < dtCopy.Rows.Count; r++)
{
for (int i = 0; i < dtCopy.Columns.Count; i++)
{
worksheet.Cells[r + 2, i + 1] = dtCopy.Rows[r][i].ToString();
}
rowRead++;
percent = ((float)(100 * rowRead)) / totalCount;
}
xlApp.Visible = true;
}
this.Close();
}
}
private void button1_Click(object sender, EventArgs e)
{
string[] FeatureName = (string[])app.FeaName;
string[] SampleName = (string[])app.SamName;
int FeatureNum = FeatureName.GetLength(0);
int SampleNum = SampleName.GetLength(0);
REngine.SetEnvironmentVariables();
REngine CLU = REngine.GetInstance();
CLU.Initialize();
NumericMatrix Freq = CLU.CreateNumericMatrix(app.FreqMatrix);
CLU.SetSymbol("Freq", Freq);
NumericMatrix Count = CLU.CreateNumericMatrix(app.CountMatrix);
CLU.SetSymbol("Count", Count);
NumericVector RFeatureNum = CLU.CreateNumeric(FeatureNum);
NumericVector RSampleNum = CLU.CreateNumeric(SampleNum);
CLU.SetSymbol("FeatureNum", RFeatureNum);
CLU.SetSymbol("SampleNum", RSampleNum);
CharacterVector RSampleName = CLU.CreateCharacterVector(app.SamName);
CharacterVector RFeatureName = CLU.CreateCharacterVector(app.FeaName);
CLU.SetSymbol("FeatureName", RFeatureName);
CLU.SetSymbol("SampleName", RSampleName);
CLU.Evaluate("CountMatrix <- as.data.frame(Count)");
CLU.Evaluate("names(CountMatrix) <- SampleName");
switch (this.comboBox1.SelectedIndex)
{
case 0:
CLU.Evaluate("d <- dist(t(CountMatrix),method = \"euclidean\")");
break;
case 1:
CLU.Evaluate("d <- dist(t(CountMatrix),method = \"maximum\")");
break;
case 2:
CLU.Evaluate("d <- dist(t(CountMatrix),method = \"manhattan\")");
break;
case 3:
CLU.Evaluate("d <- dist(t(CountMatrix),method = \"canberra\")");
break;
case 4:
CLU.Evaluate("d <- dist(t(CountMatrix),method = \"binary\")");
break;
case 5:
CLU.Evaluate("d <- dist(t(CountMatrix),method = \"minkowski\")");
break;
default:
break;
}
switch (this.comboBox2.SelectedIndex)
{
case 0:
CLU.Evaluate("hc <- hclust(d,method = \"ward\")");
break;
case 1:
CLU.Evaluate("hc <- hclust(d,method = \"single\")");
break;
case 2:
CLU.Evaluate("hc <- hclust(d,method = \"complete\")");
break;
case 3:
CLU.Evaluate("hc <- hclust(d,method = \"average\")");
break;
case 4:
CLU.Evaluate("hc <- hclust(d,method = \"mcquitty\")");
break;
case 5:
CLU.Evaluate("hc <- hclust(d,method = \"median\")");
break;
case 6:
CLU.Evaluate("hc <- hclust(d,method = \"centroid\")");
break;
default:
break;
}
CLU.Evaluate("plot(hc)");
this.Close();
}
