private void linkLoadFromFile_LinkClicked(object sender, LinkLabelLinkClickedEventArgs e)
{
try
{
DialogResult dlg = dlgOpenQuantification.ShowDialog();
if (dlg != DialogResult.OK)
{
return;
}
SetText(dlgOpenQuantification);
string filename = dlgOpenQuantification.FileName;
if (System.IO.File.Exists(filename))
{
PA = FileUtil.ReadPermutationArrayQuantificationData(filename);
LoadQuantificationFromPermutationArrayToGrid();
dgPeptides.RowCount = dgPeptides.ColumnCount = 0;
thresholdEntry.SetInitialValues(PA.GetPositiveThreshold(), PA.GetNegativeThreshold());
Run();
}
}
catch
{
MessageBox.Show("There is a problem with loading the quantification file.\r\nPlease make sure the quantification data is the only data in the loaded file.\r\n", Application.ProductName);
}
}
private void LoadProject()
{
try
{
DialogResult dlg = dlgOpenProject.ShowDialog();
if (dlg != DialogResult.OK)
{
return;
}
SetText(dlgOpenProject);
string filename = dlgOpenProject.FileName;
PA = PermutationArray.ReadFromFile(filename);
thresholdEntry.SetInitialValues(PA.GetPositiveThreshold(), PA.GetNegativeThreshold());
cbWildTypeXAxis.Checked = !PA.PermutationXAxis;
cbYAxisTopToBottom.Checked = PA.WildTypeYAxisTopToBottom;
colCount = PA.ColCount;
rowCount = PA.RowCount;
SetRowColumnCount();
rbMeanValue.Checked = PA.NormMode == NormalizationMode.Mean;
rbPerRowColumn.Checked = PA.NormMode != NormalizationMode.Mean;
if (PA.PeptideMatrix != null)
{
LoadPeptidesFromPermutationArrayToGrid();
}
if (PA.QuantificationMatrix != null)
{
LoadQuantificationFromPermutationArrayToGrid();
}
if (PA.NormalizedMatrix != null)
{
LoadNormalizedMatrixFromPeptideArrayToGrid();
}
bool gridsOK = ColorGrids();
eNotes.Text = PA.Notes;
imageReference.Image = null;
try
{
Image img = FileUtil.Base64ToImage(PA.ImageStr);
imageReference.Image = img;
}
catch { }
DrawColorMatrix();
if (!gridsOK)
{
MessageBox.Show("There is a problem in loading the file. It is highly recommended to re-run the analysis.", Analyzer.ProgramName);
}
}
catch
{
MessageBox.Show("There is a problem in loading the file. It is highly recommended to re-run the analysis.", Analyzer.ProgramName);
}
linkRun.Visible = true;
}
private void Run()
{
string[,] values = new string[dgQuantification.RowCount, dgQuantification.ColumnCount];
for (int iRow = 0; iRow < dgQuantification.RowCount; iRow++)
{
for (int iCol = 0; iCol < dgQuantification.ColumnCount; iCol++)
{
values[iRow, iCol] = dgQuantification[iCol, iRow].Value?.ToString() ?? "";
}
}
bool xPossible = true, yPossible = true;
PermutationArray.CheckPermutationAxis(values, ref xPossible, ref yPossible);
if (xPossible && !yPossible)
{
cbWildTypeXAxis.Checked = false;
}
else if (yPossible && !xPossible)
{
cbWildTypeXAxis.Checked = true;
}
else if (!xPossible && !yPossible)
{
MessageBox.Show("Please make sure one the axes have permutation array (each amino acid has to exist at most once)", Analyzer.ProgramName);
return;
}
;
PA = new PermutationArray(values, !cbWildTypeXAxis.Checked, cbYAxisTopToBottom.Checked, out List <string> warnings, out string error);
if (error != "")
{
MessageBox.Show(error, Analyzer.ProgramName);
return;
}
if (warnings.Count > 0)
{
warnings.Insert(0, "Warning:");
MessageBox.Show(String.Join("\r\n", warnings), Analyzer.ProgramName);
}
PA.SetPositiveThreshold(thresholdEntry.PositiveThreshold, out bool negChanged);
PA.SetNegativeThreshold(thresholdEntry.NegativeThreshold, out bool posChanged2);
LoadPeptidesFromPermutationArrayToGrid();
LoadNormalizedMatrixFromPeptideArrayToGrid();
dgPeptides.Rows[0].DefaultCellStyle = dgPeptides.ColumnHeadersDefaultCellStyle;
dgPeptides.Columns[0].DefaultCellStyle = dgPeptides.ColumnHeadersDefaultCellStyle;
dgNormalized.Rows[0].DefaultCellStyle = dgPeptides.ColumnHeadersDefaultCellStyle;
dgNormalized.Columns[0].DefaultCellStyle = dgPeptides.ColumnHeadersDefaultCellStyle;
ColorGrids();
DrawColorMatrix();
}
private void btnSave_Click(object sender, EventArgs e)
{
dlgSaveProject.FileName = ProjectName;
DialogResult dlg = dlgSaveProject.ShowDialog();
if (dlg != DialogResult.OK)
{
return;
}
PA.Notes = eNotes.Text;
PA.ImageStr = FileUtil.ImageToBase64(imageReference.Image);
SetText(dlgSaveProject);
string filename = dlgSaveProject.FileName;
if (PermutationArray.SaveToFile(filename, PA))
{
MessageBox.Show(filename + " is saved", Analyzer.ProgramName);
}
}
/// <summary>
/// Dictionary of discrimination factor for each char at every position: D = Avrg(v[i!=j]) / v[i] - 1
/// </summary>
/// <param name="PA"></param>
/// <returns></returns>
static public Dictionary <int, Dictionary <char, double> > GenerateDiscriminationFactors(PermutationArray PA, out List <char> ExistingAminoAcids)
{
ExistingAminoAcids = new List <char>();
try
{
Dictionary <int, double> totalWeightsPerPos;
Dictionary <int, Dictionary <char, double> > weights;
int pepsize = PA.ModifiedPeptides[0].Length;
totalWeightsPerPos = new Dictionary <int, double>();
weights = new Dictionary <int, Dictionary <char, double> >();
for (int i = 0; i < pepsize; i++)
{
totalWeightsPerPos.Add(i, 0);
weights.Add(i, new Dictionary <char, double>());
}
foreach (string s in PA.ModifiedPeptides)
{
for (int i = 0; i < pepsize; i++)
{
char c = s[i];
if (!ExistingAminoAcids.Contains(c))
{
ExistingAminoAcids.Add(c);
}
if (c == PA.WildTypePeptide[i])
{
if (weights[i].ContainsKey(c))
{
continue; //skip wildtype char if already added
}
}
double weight = PA.PeptideWeights[s];
totalWeightsPerPos[i] += weight;
weights[i].Add(c, weight);
break;//there can be one aa change per peptide
}
}
for (int i = 0; i < pepsize; i++)
{
List <char> charlist = weights[i].Keys.ToList();
foreach (char c in charlist)
{
weights[i][c] /= totalWeightsPerPos[i];
/*double curWeight = weights[i][c];
* double avrRest = (totalWeightsPerPos[i] - curWeight) / (weights[i].Count - 1);
* if (curWeight == avrRest)
* weights[i][c] = 1;
* else
* weights[i][c] = curWeight / (curWeight - avrRest); //avrRest / curWeight - 1;*/
}
}
return(weights);
}
catch (Exception exc)
{
//Logger.Log(LogEntryType.SevereException, exc);
return(null);
}
}
