private string displayHeatMapData(AlignmentResult alignmentResult)
{
var sb = new StringBuilder();
for (var i = alignmentResult.AlignmentHeatmapScores.GetLength(1) - 1; i >= 0; i--)
{
for (var k = 0; k < alignmentResult.AlignmentHeatmapScores.GetLength(0); k++)
{
sb.Append(alignmentResult.AlignmentHeatmapScores[k, i]);
sb.Append("\t");
}
sb.Append(Environment.NewLine);
}
return(sb.ToString());
}
public clsAlignmentFunction GetAlignment(List <TargetBase> massTagList, List <TargetedResultDTO> featuresToAlign)
{
var multialignMassTagDB = new clsMassTagDB();
//TODO: I might be able to dynamically update these values. Take my foundFeatures and calculate their avg PPMDiff. Then use that info here.
var alignmentOptions = new clsAlignmentOptions();
alignmentOptions.MassCalibrationWindow = this.AlignerParameters.MassCalibrationWindow; //note - it seems that 50 ppm is used as a default setting in VIPER.
alignmentOptions.ContractionFactor = this.AlignerParameters.ContractionFactor;
alignmentOptions.IsAlignmentBaselineAMasstagDB = this.AlignerParameters.IsAlignmentBaselineAMassTagDB;
alignmentOptions.MassBinSize = this.AlignerParameters.MassBinSize;
alignmentOptions.MassCalibrationLSQNumKnots = this.AlignerParameters.MassCalibrationLSQNumKnots;
alignmentOptions.MassCalibrationLSQZScore = this.AlignerParameters.MassCalibrationLSQZScore;
alignmentOptions.MassCalibrationMaxJump = this.AlignerParameters.MassCalibrationMaxJump;
alignmentOptions.MassCalibrationMaxZScore = this.AlignerParameters.MassCalibrationMaxZScore;
alignmentOptions.MassCalibrationNumMassDeltaBins = this.AlignerParameters.MassCalibrationNumMassDeltaBins;
alignmentOptions.MassCalibrationNumXSlices = this.AlignerParameters.MassCalibrationNumXSlices;
alignmentOptions.MassCalibrationUseLSQ = this.AlignerParameters.MassCalibrationUseLSQ;
alignmentOptions.MassCalibrationWindow = this.AlignerParameters.MassCalibrationWindow;
alignmentOptions.MassTolerance = this.AlignerParameters.MassToleranceForNETAlignment;
alignmentOptions.MaxPromiscuity = this.AlignerParameters.MaxPromiscuity;
alignmentOptions.MaxTimeJump = this.AlignerParameters.MaxTimeJump;
alignmentOptions.NETBinSize = this.AlignerParameters.NETBinSize;
alignmentOptions.NETTolerance = this.AlignerParameters.NETTolerance;
alignmentOptions.NumTimeSections = this.AlignerParameters.NumTimeSections;
alignmentOptions.UsePromiscuousPoints = this.AlignerParameters.UsePromiscuousPoints;
var processor = new clsAlignmentProcessor();
processor.AlignmentOptions = alignmentOptions;
var multiAlignMassTags = convertDeconToolsMassTagsToMultialignMassTags(massTagList);
multialignMassTagDB.AddMassTags(multiAlignMassTags);
processor.SetReferenceDatasetFeatures(multialignMassTagDB);
var multialignUMCs = convertDeconToolsLCMSFeaturesToMultialignFeatures(featuresToAlign);
processor.SetAligneeDatasetFeatures(multialignUMCs, alignmentOptions.MZBoundaries[0]);
processor.PerformAlignmentToMSFeatures();
this.Result = getResultsForAlignment(processor);
return(processor.GetAlignmentFunction());
}
private AlignmentResult getResultsForAlignment(clsAlignmentProcessor processor)
{
float[] scanLCValues = null;
float[] NETValues = null;
float[,] scores = null;
processor.GetAlignmentHeatMap(ref scores, ref scanLCValues, ref NETValues);
var result = new AlignmentResult();
result.ScanLCValues = scanLCValues;
result.NETValues = NETValues;
result.AlignmentHeatmapScores = scores;
//get massResiduals_vs_scan and massResiduals_vs_m/z
var residuals = processor.GetResidualData();
result.Mass_vs_scan_ResidualsBeforeAlignment = residuals.massError;
result.Mass_vs_scan_ResidualsAfterAlignment = residuals.massErrorCorrected;
result.Mass_vs_scan_ResidualsScanValues = residuals.scans;
result.Mass_vs_mz_ResidualsBeforeAlignment = residuals.mzMassError;
result.Mass_vs_mz_ResidualsAfterAlignment = residuals.mzMassErrorCorrected;
result.Mass_vs_mz_ResidualsMZValues = residuals.mz;
//get stats on variability
result.NETStDev = processor.GetNETStandardDeviation();
result.NETAverage = processor.GetNETMean();
result.MassAverage = processor.GetMassMean();
result.MassStDev = processor.GetMassStandardDeviation();
double[,] massHistogramData = null;
double[,] netHistogramData = null;
double[,] driftHistogramData = null;
processor.GetErrorHistograms(0.1, 0.002, 0.1, ref massHistogramData, ref netHistogramData, ref driftHistogramData);
result.massHistogramData = massHistogramData;
result.NETHistogramData = netHistogramData;
return(result);
}
public void Result([FromBody] string JobResult)
{
AlignmentResult AlignmentResultFormGrid = JsonConvert.DeserializeObject <AlignmentResult>(JobResult);
string Email = Repo.GetEmailByAlingmnetJobId(AlignmentResultFormGrid.JobId);
string Decrypted = Serializer.Decrypt(AlignmentResultFormGrid.Result, "ResultComputing");
Repo.FinalizeJob(AlignmentResultFormGrid.JobId, Decrypted);
MailMessage EMailMessage = new MailMessage("*****@*****.**", Email);
EMailMessage.Subject = "Grid Notification";
EMailMessage.IsBodyHtml = true;
EMailMessage.Body = $"We Have done your Alignment Job, you can check it out in your history page! <a href='http://mtidna.azurewebsites.net/Display/{AlignmentResultFormGrid.JobId}'> Check my History Now </a>";
SmtpClient SC = new SmtpClient("smtp.gmail.com", 587);
SC.DeliveryMethod = SmtpDeliveryMethod.Network;
SC.Credentials = new NetworkCredential("*****@*****.**", "Mti_dna2017");
SC.EnableSsl = true;
SC.Send(EMailMessage);
}
/// <summary>
/// Main Edlib method.
/// </summary>
/// <param name="originalQuery">String a</param>
/// <param name="originalTarget">String b</param>
/// <param name="config">Configuration</param>
/// <returns>Result of the alignment</returns>
public static AlignmentResult Align(string originalQuery, string originalTarget, AlignmentConfig config)
{
// NOTE: Is other mode useful? If so, why?
if (config.Mode == AlignmentMode.Hw || config.Mode == AlignmentMode.Shw)
{
throw new NotImplementedException();
}
AlignmentResult result = new AlignmentResult
{
Status = (int)AlignmentStatus.Ok,
EditDistance = -1,
EndLocations = null,
StartingLocations = null,
NumberOfLocations = 0,
Alignment = null,
AlignmentLength = 0,
AlphabetLength = 0,
};
// Transform sequences and recognize alphabet
byte[] query, target;
string alphabet = TransformSequences(originalQuery, originalTarget, out query, out target);
result.AlphabetLength = alphabet.Length;
// Initialization
int queryLength = originalQuery.Length;
int targetLength = originalTarget.Length;
int maxBlocks = CeilDivision(queryLength, WordSize);
int w = maxBlocks * WordSize - queryLength;
EqualityDefinition equalityDefinition = new EqualityDefinition(alphabet, config.AdditionalEqualities,
config.AdditionalEqualitiesLength);
ulong[] peq = BuildPeq(alphabet.Length, query, queryLength, ref equalityDefinition);
// Main Calculation
int positionNw = -1;
AlignmentData alignmentData = new AlignmentData();
bool dynamicK = false;
int k = config.K;
if (k < 0) // If valid k is not given, auto-adjust k until solution is found.
{
dynamicK = true;
k = WordSize; // Gives better results than smaller k.
}
do
{
MyersEditDistanceNw(peq, w, maxBlocks, queryLength, target, targetLength, k, false, -1,
ref result.EditDistance, ref positionNw, ref alignmentData);
k *= 2;
} while (dynamicK && result.EditDistance == -1);
// NOTE: Do we need this block code? We only care about editing distance
// Since we only care about the editing distance score, this is where we stop
if (result.EditDistance >= 0)
{
// If NW mode, set end location explicitly.
if (config.Mode == AlignmentMode.Nw)
{
result.EndLocations = new int[sizeof(int) * 1];
result.EndLocations[0] = targetLength - 1;
result.NumberOfLocations = 1;
}
// if (!(config.Task == AlignmentTask.TaskLocate || config.Task == AlignmentTask.TaskPath))
// {
// for (int i = 0; i < result.NumberOfLocations; i++) {
// result.StartingLocations[i] = 0;
// }
// }
}
return(result);
}