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TIGR Spotfinder: a tool for microarray image processing

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Presentation on theme: "TIGR Spotfinder: a tool for microarray image processing"— Presentation transcript:

1 TIGR Spotfinder: a tool for microarray image processing
Developer: Vasily Sharov Presenter: John Braisted The Institute for Genomic Research THE INSTITUTE FOR GENOMIC RESEARCH TIGR

2 Microarray Data Flow Image Analysis Normalization / Filtering
Printer Scanner .tiff Image File Image Analysis Raw Gene Expression Data Gene Annotation Normalization / Filtering Database AGED Others… MAD Normalized Data with Gene Annotation Expression Analysis Interpretation of Analysis Results

3 Process Overview Sample1 mRNA Sample2 mRNA Cy3 intensity Cy3 RT
Cy5-cDNA Cy3-cDNA RT RT cDNA array Cy5 intensity Sample2 mRNA

4 Basic Steps from Image to File
1.) Image File Loading 2.) Construct or Apply an Overlay Grid 3.) Computations Find Spot Boundary and Area Intensity Calculation Background Calculation and Correction 4.) Quality Control 5.) Text File Output

5 Basic Demonstration Exploring the Interface (Using An Existing Grid File)

6 Microarray Image Parameters
MA Scanner generates two 16 bit gray scale TIFF images: one image for each labeling probe (Cy3 and Cy5) 16 bit schema provides signal dynamic range from 0 to 216=65536 Each image size varies from 20 to 30 MB for scanning resolution 10 mm/pixel

7 Typical layout of microarray image
Image size 22 MB Image size MB (images scanned at 10mm/pix resolution)

8 Processing Overview Apply the Grid Determine Spot Boundary
Determine Background and Correct Intensity Calculate Spot Intensity

9 Applying an Overlay Grid
What does it accomplish? The grid cells set a boundary for the spot finding algorithms. The grid cells also define an area for background correction.

10 Gridding Dimension Parameters
pin X pin X pin Y pin Y

11 Spot Spacing Parameter

12 Spot Finding Spot finding requires an estimated spot size.
The spot can be drawn as an irregular contour, as an ellipse, or as unconnected pixels. Area inside contour is used for spot intensity calculation Area outside contour is used for local background calculation

13 Processing Overview Apply the Grid Determine Spot Boundary
Calculate Spot Intensity Determine Background and Correct Intensity

14 Background Calculation
Background intensity is calculated as the median pixel intensity from the area within the square and outside the spot. A separate local background is calculated for each spot using the non-spot pixels from it’s square. local background area

15 Spot Definition and Calculations
Spot Area, A = number of pixels within the defined spot boundary BKG = median pixel value within the cell (excluding the spot pixels) Integral = Sum of all spot pixels excluding saturated pixels Reported “Intensity”=Integral-BKG*A

16 Spot Integration with Background Correction

17 Intensity Calculation Formula
= pixel intensity for pixel i = number of pixels in the spot = median background pixel value = number of non-saturated pixels in spot

18 Quality Control Issues
Two measures of spot quality are reported by SpotFinder: Saturation Factor QC Score; (Reports shape and signal to noise ratio.)

19 Saturation Examples Partially saturated spots can look like this:
saturated area non-saturated area Completely saturated spots can look like this: fully saturated spot

20 Saturation, Pixel Value Limit
Output: pixel value 216=65536 Input: fluorescence dye light signal

21 (total number of spot pixels)
Saturation Factor Saturation Factor = (# good pixels in spot) (total number of spot pixels) -Partially saturated spots can be handled in SpotFinder by excluding the saturated pixels from spot area and intensity calculations. -Fully saturated spots can not be recovered in SpotFinder. In this case rescanning with lower excitation power or PMT gain could be considered. *Faint spots may possibly be lost.

22 Saturation, RI Plot RI plot: log(IB/IA) vs 1/2log(IA*IB)
clearly displays the saturation limits

23 Quality Control, QC Score
A QC Score is generated for each spot and is based on the spot shape and a measure of signal to noise ratio. QC Score QCA QCB shape signal/noise shape signal/noise

24 Shape Factor = (Spot Area/Perimeter)
Spot Shape Parameter Shape Factor = (Spot Area/Perimeter) Spots with large perimeters relative to spot area will have a low shape factor.

25 *med(BKG) + * SD(BKG)
Signal to Noise Ratio 216 S/N factor = fraction of spot pixels exceeding: *med(BKG) + * SD(BKG) Pixel Values med(BKG)

26 Quality Control Calculation
QC Score = (QCA+QCB)/2 QCA=sqrt(QC shape*QC S/N) for channel A QCB=sqrt(QC shape*QC S/N) for channel B

27 Quality Control, RI Plot
log(IB/IA) vs1/2log(IA*IB) plotted for means shows clearly low intensity distortion due to background overestimation. Data from earlier slide processed without QC filter

28 Quality Control (data provided by E. Snesrud)

29 Quality Control (data provided by E. Snesrud)

30 SpotFinder Flag Descriptions
A - The number of non-saturated pixels in spot is 0 B - Number of non-saturated pixels in spot is between 0 and 50 C - Number of non saturated pixels in spot is more then 50 X - Spot was detected and rejected based on spot shape and spot intensity relative to surrounding background Y- Spot background is higher than spot intensity Z - Spot was not detected by the program

31 Demonstration Grid Construction


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