IMAGE INFORMATICS SOLUTIONS Extracting Information From Images Array-Pro 4.5 Training, May 2003

Array-Pro Analyzer

Experiment Model Template concept Experiment definition Default parameters Demo macro: Create Grid Finding Template

Experiment Driven

Image Acquisition From scanner From files

Image Examination Overall image quality On-screen optimization Understanding the intended grid layout Spot shape

General Image Analysis Tools Contrast enhancement AOI Navigation and zoom Colorize/color channel Filters Operations Convert/duplicate Surface plot

Template Method Development Conceptual framework Rotation Grid location line distance AOI (bounding rectangle) Spot location algorithms Sub-grid definition Cell boundary definition Multiple grid zones Hands on practice

Spot location definition –On the first image (creating a template) –On other images Background correction technique Normalization technique Greatest Image Analysis Error Sources

Spot ID Wizard

Auto Grid/Spot Detection Parameters

Advanced Detection

Grid Adjustment Manual Save/load/copy/paste Auto align Using Extended auto-align

Spot Descriptors ASCII input GAL files URL lookup

Replicates within an experiment Adjacent Free assignment By sub-grid By labels

How Do You Know Whether Your Data Is Good? Replicates –Is it reproducible within acceptable error? –A tenet of science Standards –No gold standard –Even housekeeping genes change under most experimental conditions –Does it compare favorably to Northern blots?

Replicate Handling in Array-Pro

Replicates (Cont)

Replicate Reporting With so many variables with microarrays, instead of trying to interpret a bad spot image (making assumptions that may not be valid), bad data can be discarded yet still have enough for analysis

Measurements Conceptual framework Primary vs. informational measurements Meaning of Net intensity and background

Measurements & Statistics Available at four levels –Spots –Replicates –Image groups –Collections of image groups

Measurements & Descriptors

Spot Measurements

Image Group Measurements

Quality Metrics User definable Some common ones –Standard deviation of the background pixels –Inertia diameter (indication of spot shape/uniformity) –Spot shift –Number of pixels within threshold

Quality Metrics Spot quality metrics User-defined parameters Automatic cell flagging Array quality metrics

Optimized Results Only cells failing quality metrics removed; ratio near expected; mean and median ratio close

Scatter-plot Display Default method; good but wide variation at low signal; Cy5 signal strength causes distortion Optimized results with much less variance at low signal; excellent linearity

View and Labels User feedback definition Color assignment

Signal Optimization Background concept Background methods Net intensity definition as found in measurements data table

Background Characterization

Appropriate Noise Treatment Not as many cells ignored Using statistical parameters: –Mean, Median, Ranked percentile, Trimmed mean Background methods Pre-filtering Net intensity definition as found in measurements data table

Using Local Corners About the same

Normalization Theory Methods

Normalization methods

Greatest Sources of Image Acquisition Error Garbage In  Garbage Out –Image analysis can only go so far Dynamic range imbalance of Cy5/Cy3 –Take advantage of 65,536 counts of a 16-bit image Saturation –Pixels truncate at the top end Bleaching –Due to high laser intensity Optics Mechanics

Major Factors Influencing Fluorescent Intensity Readings Particulate reflection –Typically 2 to 100 X compared to highest fluorescent signal Temperature pH Oxygen Buffer strength Analyte concentration Time Hybridization efficiency –Kinetics, depletion, etc.

CY3/Cy5 Intensity Curves

Background/Normalization Correction

Data Windows Scatterplot Data table Histogram Cell window Data Graph Information table

Cell Groups Standard Custom Derived Automatic cell flagging

Cell Groups One can put any group of cells into groups for interpretation

Histogram Any measurement or cell group can be displayed; interactive with all other data display windows

Cell Window

Scatter Plot

Data Graph

Data Table For information to sort cells and for reporting

Statistical Feedback

Info Table (Cells)

Info Table (Images)

Cell Group Information

Image Groups Hierarchy Labels

Macro Programming Demo macros Macro recorder Sample macros

Selling Feature/benefits Demonstration –Overview presentation Demo movies Demo macros –In-depth technical selling to qualified prospects

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