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MCGH Analyzer Software: DNA Data Processing Steps

Explore MCGH Analyzer software for DNA chip data processing including background reduction, quality control, spot accumulation, and main calculation loop. Enhance clone selection and ratios analysis with new features.

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MCGH Analyzer Software: DNA Data Processing Steps

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  1. MCGH Analyzer Hans A. Kestler André Müller MCGH Analyzer

  2. Data processing steps • Scanning of the DNA chips (normal and switched) • 2 Channels (Cy 5 and Cy 3) • Build mean/median over the pixels • Further processing with MCGH Software MCGH Analyzer

  3. MCGH software • Background reductioncalculate intensities according to the background • Quality control of the spotsreject spots not fitting the quality criteria • Accumulate spots to clones • Check testreject clones not fitting the visual options • Select control clones • Reduce control clones • Main calculation loop MCGH Analyzer

  4. Overview MCGH Analyzer

  5. Background reduction Background reduction to get intensities • No reduction • Fixed reduction • Local reduction • Global reduction • Local + Fixed reduction • Global + Fixed reduction Compute log Ratios • log( IntCy3 / IntCy5 ) • log( IntCy5 / IntCy3 ) MCGH Analyzer

  6. Quality control Reject spots with • flags marked by the scanning software(bad, not found, absent, normal ...) • A background intensity brighter than the foreground (new!) • Min/Max reduction: • Reject the n smallest ratios • Reject the n largest ratios MCGH Analyzer

  7. Spots to clones Accumulate the non-rejected spot values • Mean • Standard deviation • Median over • Intensities (Cy3, Cy5) • log Ratios New Feature:Reject clones with less than SpotLowerBound valid spots. MCGH Analyzer

  8. Check test Reject clones if at least one of these conditions holds: • Me(di)an background intensity > Background upper bound • Me(di)an Cy3 Intensity < Me(di)an Cy3 background intensity x Intensity lower bound • Standard deviation Cy3 Ratio > Ratio SD upper bound MCGH Analyzer

  9. Select control clones Only non-rejected clones will be selected as control clones. • Manual selectionSelect clones with id = ‚91‘ or ‚k‘ or ‚K‘ or ‚?91‘ as control clone • Automatic selection • No [AutoBand][CutoffPercentage] clones from the middle band • [AutoBand]Select band around the median MCGH Analyzer

  10. Reduce control clones Some of the control clones will be rejected ... • [Cutoff Percentage]Reject the n smallest ratios • Without [Cutoff Band]Reject the n largest ratios • [Cutoff Band]Reject band around the median MCGH Analyzer

  11. Main calculation loop • Calculate control means (the mean/median over all control clones/spots) • Normalize ratios (subtract control mean from the ratio) • Calculate tolerance value Ts standard deviation of the ratios of the observed clonenthe number of valid spots in this clonet value of the t-statistic significance niveau • [ Force T-Test ]Reject clones with T > [ Force T Value ] • [ C Check ]Replace tolerance values with possible greater values. • Find clone with maximum tolerance and reject it if its tolerance value T is > [ Force T Value ] • Perform [ T Test ] and evaluate result value. Everything has to be recalculated if a control clone will be rejected. MCGH Analyzer

  12. The C Check The clone tolerance values are now recalculated according to the following scheme: If the new tolerance value is greater than the old T will be replaced by the new value MCGH Analyzer

  13. The T Test If [ Force T ] is set, the value will be set to the [ Force T Value ] otherwise it is the greates tolerance value found in the clones. MCGH Analyzer

  14. The T Test (2) Calculation of the result value R • [ T Test ] • No [ T Test ] : thresholding In this routine the test T > [ Force T Value ] will be performed repeatedly MCGH Analyzer

  15. NCBI Clone Database • Integration of the NCBI “component” database • Automatically mapping of clone id’s to accession numbers, genomic clone locations and clone status information according to an up-to-date database • Direct import of the NCBI file format MCGH Analyzer

  16. Database-generated Information Accession-Number Start-Base End-Base Clone-State MCGH Analyzer

  17. Batch Processing • One ore more file pairs can be added to a session • All computations are performed simultaneous on the included datasets MCGH Analyzer

  18. Diagrams functions • Ratio-profiles of multiple clone sets can be shown in one diagram MCGH Analyzer

  19. Ideogram Browser 1 • Independent portable Java application • Automation from MCGH-Analyzer with JNI • Generation of ideogram drawings from the NCBI map database • Direct representation of gain and lost markers of multiple clone sets • Scalable and scrollable graphs MCGH Analyzer

  20. Ideogram Browser 2 MCGH Analyzer

  21. Software Structure 1 • Excel as convenient platform with widely known user interface for • Table representation • Diagram drawing • User interaction • Windows DLL written in C++ for high performance using COM automation • Platform-independent Java-Application for visualizing ideograms (can be docked to the DLL via JNI) MCGH Analyzer

  22. Software Structure 2 MCGH Analyzer

  23. Future Features • Copy number estimation • Global thresholds • Adaptive (local) thresholds • Wavelets • Adaptive weights smoothing • NCBI database online update • Interface to the R platform MCGH Analyzer

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