private void mnuOpen_Click(object sender, EventArgs e)
{
var dlg = new ITraqOpenFileDialog();
dlg.LoadOption();
if (dlg.ShowDialog(this) == System.Windows.Forms.DialogResult.OK)
{
proteinFile = dlg.ProteinFile;
itrapFile = dlg.ITraqFile;
var paramFile = Path.ChangeExtension(dlg.ProteinFile, "param");
if (!File.Exists(paramFile))
{
MessageBox.Show(this, "Error find parameter file " + paramFile);
return;
}
option = new ITraqProteinStatisticOption();
option.LoadFromFile(paramFile);
Progress.Begin();
var task = Task.Factory.StartNew(() => LoadData(), TaskCreationOptions.LongRunning);
task.ContinueWith((m) => this.Invoke(new Action(UpdateData)), TaskContinuationOptions.OnlyOnRanToCompletion);
}
}
public ITraqUniquePeptideStatisticBuilder(ITraqProteinStatisticOption option, bool isSiteLevel, string fastaFile, IAccessNumberParser parser)
: base(option)
{
this.isSiteLevel = isSiteLevel;
this.fastaFile = fastaFile;
this.parser = parser;
}
protected ITraqProteinStatisticOption GetStatisticOption()
{
ITraqProteinStatisticOption option = new ITraqProteinStatisticOption();
option.DatasetMap = pnlClassification.GetClassificationSet();
option.ITraqFileName = iTraqFile.FullName;
option.MinimumProbability = filterPeptide.Checked ? minProbability.Value : 0.0;
option.NormalizeByMedianRatio = normalize.Checked;
option.RatioPeptideToProteinBuilder = builders.SelectedItem;
option.QuantifyModifiedPeptideOnly = modifiedPeptideOnly.Checked;
option.ModificationChars = modifiedChar.Text;
option.References = itraqIons.GetFuncs();
return(option);
}
public void Update(object sender, UpdateQuantificationItemEventArgs e)
{
ITraqProteinStatisticOption option = e.Option as ITraqProteinStatisticOption;
IIdentifiedProteinGroup protein = null;
if (e.Item is IEnumerable <IIdentifiedSpectrum> )
{
var spectra = e.Item as IEnumerable <IIdentifiedSpectrum>;
protein = new IdentifiedProteinGroup();
protein.Add(new IdentifiedProtein());
protein[0].Peptides.AddRange(from s in spectra select s.Peptide);
}
else if (e.Item is IIdentifiedProteinGroup)
{
protein = e.Item as IIdentifiedProteinGroup;
}
if (protein == null)
{
throw new ArgumentException("e.Item should be IIdentifiedProteinGroup or IEnumerable<IIdentifiedSpectrum>");
}
var validItem = protein[0].Peptides.FirstOrDefault(m =>
{
var item = m.Spectrum.FindIsobaricItem();
return(null != item && item.Valid);
});
if (null == validItem)
{
zgcGraph.ClearData(true);
return;
}
var masterPane = zgcGraph.InitMasterPanel(g, 1, title, this.pl);
var panel = masterPane[0];
var samples = option.GetSamples(validItem.Spectrum.FindIsobaricItem().PlexType);
var dsNames = option.DatasetMap.Keys.OrderBy(m => m).ToList();
var ratioCalc = option.GetRatioCalculator();
xlabels.Clear();
double index = 0.0;
string outlierStr = "Outlier";
string proteinStr = "Protein Ratio";
foreach (var dsName in dsNames)
{
var expNames = new HashSet <string>(option.DatasetMap[dsName]);
foreach (var sample in samples)
{
index += 1.0;
ratioCalc.GetSample = sample.GetValue;
ratioCalc.DatasetName = dsName;
ratioCalc.ChannelName = sample.ChannelRatioName;
ratioCalc.Filter = m => expNames.Contains(m.Query.FileScan.Experimental);
var ratios = ratioCalc.Calculate(protein);
xlabels.Add(dsName + ":" + sample.Name);
if (ratios.Count > 0)
{
var ratio = protein[0].FindITraqChannelItem(dsName, sample.ChannelRatioName).Ratio;
PointPairList pplNormal = new PointPairList();
PointPairList pplOutlier = new PointPairList();
PointPairList pplProteinRatio = new PointPairList();
foreach (var r in ratios)
{
if (r.IsOutlier)
{
pplOutlier.Add(new PointPair(index, Math.Log(r.Ratio)));
}
else
{
pplNormal.Add(new PointPair(index, Math.Log(r.Ratio)));
}
}
pplProteinRatio.Add(new PointPair(index, Math.Log(ratio)));
panel.AddPoints(pplProteinRatio, Color.Red, proteinStr);
if (pplOutlier.Count > 0)
{
panel.AddPoints(pplOutlier, Color.Green, outlierStr);
outlierStr = string.Empty;
}
panel.AddPoints(pplNormal, Color.Black);
proteinStr = string.Empty;
}
}
}
panel.XAxis.ScaleFormatEvent += new Axis.ScaleFormatHandler(XAxis_ScaleFormatEvent);
panel.XAxis.Scale.Min = 0.0;
panel.XAxis.Scale.Max = index + 1.0;
panel.XAxis.Scale.FontSpec.Angle = 90;
panel.YAxis.Title.Text = "log(Ratio)";
ZedGraphicExtension.UpdateGraph(zgcGraph);
}
public AbstractITraqProteinStatisticBuilder(ITraqProteinStatisticOption option)
{
this.option = option;
this.ratioCalc = option.GetRatioCalculator();
}
public void Update(object sender, UpdateQuantificationItemEventArgs e)
{
ITraqProteinStatisticOption option = e.Option as ITraqProteinStatisticOption;
IIdentifiedProteinGroup protein = null;
if (e.Item is IEnumerable <IIdentifiedSpectrum> )
{
var spectra = e.Item as IEnumerable <IIdentifiedSpectrum>;
protein = new IdentifiedProteinGroup();
protein.Add(new IdentifiedProtein());
protein[0].Peptides.AddRange(from s in spectra select s.Peptide);
}
else if (e.Item is IIdentifiedProteinGroup)
{
protein = e.Item as IIdentifiedProteinGroup;
}
if (protein == null)
{
throw new ArgumentException("e.Item should be IIdentifiedProteinGroup or IEnumerable<IIdentifiedSpectrum>");
}
var validItem = protein[0].Peptides.FirstOrDefault(m =>
{
var item = m.Spectrum.FindIsobaricItem();
return(null != item && item.Valid);
});
if (null == validItem)
{
zgcGraph.ClearData(true);
return;
}
var masterPane = zgcGraph.InitMasterPanel(g, 1, title, this.pl);
var panel = masterPane[0];
var samples = option.GetSamples(validItem.Spectrum.FindIsobaricItem().PlexType);
var dsNames = option.DatasetMap.Keys.OrderBy(m => m).ToList();
var ratioCalc = option.GetRatioCalculator();
List <string> xlabels = new List <string>();
List <PointPairList> outliers = new List <PointPairList>();
List <PointPairList> normals = new List <PointPairList>();
PointPairList proteins = new PointPairList();
//按照数据集循环
foreach (var dsName in dsNames)
{
var expNames = new HashSet <string>(option.DatasetMap[dsName]);
//按照样品循环
foreach (var sample in samples)
{
ratioCalc.GetSample = sample.GetValue;
ratioCalc.DatasetName = dsName;
ratioCalc.ChannelName = sample.ChannelRatioName;
ratioCalc.Filter = m => expNames.Contains(m.Query.FileScan.Experimental);
var ratios = ratioCalc.Calculate(protein);
//添加相应的分类名
xlabels.Add(dsName + ":" + sample.Name);
//每个分类有三种数据：outlier,normal和proteinratio
var outlier = new PointPairList();
outliers.Add(outlier);
var normal = new PointPairList();
normals.Add(normal);
if (ratios.Count > 0)
{
var ratio = protein[0].FindITraqChannelItem(dsName, sample.ChannelRatioName).Ratio;
proteins.Add(new PointPair()
{
Y = Math.Log(ratio)
});
ratios.ForEach(m =>
{
if (m.IsOutlier)
{
outlier.Add(new PointPair()
{
Y = Math.Log(m.Ratio)
});
}
else
{
normal.Add(new PointPair()
{
Y = Math.Log(m.Ratio)
});
}
});
}
else
{
//缺失值用missing表示。
proteins.Add(new PointPair()
{
Y = PointPair.Missing
});
}
}
}
panel.AddPoints(proteins, Color.Red, "Ratio");
AddOrdinalPoints(outliers, panel, Color.Green, "Outlier");
AddOrdinalPoints(normals, panel, Color.Black, "");
panel.XAxis.Type = AxisType.Text;
panel.XAxis.Scale.FontSpec.Angle = 90;
panel.XAxis.Scale.TextLabels = xlabels.ToArray();
panel.YAxis.Title.Text = "log(Ratio)";
ZedGraphicExtension.UpdateGraph(zgcGraph);
}
public ITraqProteinStatisticBuilder(ITraqProteinStatisticOption option)
: base(option)
{
}
