MicroArray Image Analysis
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Transcript of MicroArray Image Analysis
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MicroArray Image Analysis
Robin Liechti ([email protected])www.ch.embnet.org/CoursEMBnet/CHIP02/.../Liechti02_images.ppt
statwww.epfl.ch/davison/teaching/Microarrays/lec/week04.ppt
Mark Reimers (National Cancer Institute)www.ims.nus.edu.sg/Programs/microarray/files/MReimersTut1.ppt
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Microarray analysis Array construction, hybridisation,
scanning
Quantitation of fluorescence signals
Data visualisation
Meta-analysis (clustering)
More visualisation
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Technical
probe(on chip)
sample(labelled)
pseudo-colourimage
[image from Jeremy Buhler]
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Affymetrix Gene Chip
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Images from scanner Resolution
standard 10m [currently, max 5m] 100m spot on chip = 10 pixels in diameter
Image format TIFF (tagged image file format) 16 bit (65’536 levels of
grey) 1cm x 1cm image at 16 bit = 2Mb (uncompressed) other formats exist e.g.. SCN (used at Stanford University)
Separate image for each fluorescent sample channel 1, channel 2, etc.
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Images : 2 color
cy3
cy5 Spot color Signal strength Gene expression
yellow Control = perturbed unchanged
red Control < perturbed induced
green Control > perturbed repressed
Pseudo-color overlay
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Images : 1 color
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Processing of images Addressing or gridding
Assigning coordinates to each of the spots Segmentation
Classification of pixels either as foreground or as background
Intensity extraction (for each spot) Foreground fluorescence intensity pairs (R,
G) Background intensities Quality measures
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Affymetrix Image Reading
About 100 pixels per probe cell
Selects 16-25 brightest contiguous pixels
Take average of selected pixels
Variability in best pixels ~ 5-20%
Image courtesy of Affymetrix
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Probe Variation Probes vary by two orders of
magnitude on each chip
Signal from 16 probes for the GAPDH gene on one chip
•Individual probes don’t agree on fold changes
across chips-Bright probes more often, but not always, more reliable
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Addressing
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ScanAlyze
Parameters to address the spots positions
Separation between rows and columns of grids
Individual translation of grids Separation between rows and
columns of spots within each grid Small individual translation of
spots Overall position of the array in the
image
Addressing (I) The basic structure of the
images is known (determined by the arrayer)
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Addressing (II) The measurement process
depends on the addressing procedure
Addressing efficiency can be enhanced by allowing user intervention (slow!)
Most software systems now provide for both manual and automatic gridding procedures
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http://transcriptome.ens.fr/sgdb/tools/download/image_analysis_en.pdf
Example from GenePix software
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Segmentation
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Segmentation (I) Classification of pixels as
foreground or background -> fluorescence intensities are calculated for each spot as measure of transcript abundance
Production of a spot mask : set of foreground pixels for each spot
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Segmentation (II) Segmentation methods :
Fixed circle segmentation Adaptive circle segmentation Adaptive shape segmentation Histogram segmentation
Fixed circle ScanAlyze, GenePix, QuantArray
Adaptive circle GenePix, Dapple
Adaptive shape Spot, region growing and watershed
Histogram method
ImaGene, QuantArraym DeArray and adaptive thresholding
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Fixed circle segmentation Fits a circle with a constant
diameter to all spots in the image Easy to implement The spots need to be of the same
shape and size
Bad example !
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Adaptive circle segmentation
The circle diameter is estimated separately for each spot
Dapple finds spots by detecting edges of spots (second derivative)
Problematic if spot exhibits oval shapes
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Adaptive shape segmentation Specification of starting points or seeds
Regions grow outwards from the seed points preferentially according to the difference between a pixel’s value and the running mean of values in an adjoining region.
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Histogram segmentation
Uses a target mask chosen to be larger than any other spot
Foreground and background intensity are determined from the histogram of pixel values for pixels within the masked area
Example : QuantArray Background : mean between
5th and 20th percentile Foreground : mean between
80th and 95th percentile Unstable when a large target
mask is set to compensate for variation in spot size
Bkgd Foreground
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Example from GenePix software
http://transcriptome.ens.fr/sgdb/tools/download/image_analysis_en.pdf
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Information extraction
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Spot intensity The total amount of hybridization for a
spot is proportional to the total fluorescence at the spot
Spot intensity = sum of pixel intensities within the spot mask
Since later calculations are based on ratios between cy5 and cy3, we compute the average* pixel value over the spot mask
*alternative : use ratios of medians instead of means
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Background intensity Motivation : spot’s measured intensity includes
a contribution of non-specific hybridization and other chemicals on the glass
Fluorescence from regions not occupied by DNA should by different from regions occupied by DNA -> could be interesting to use local negative controls (spotted DNA that should not hybridize)
Different background methods :Local background, morphological opening, constant background, no adjustment
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Local background Focusing on small regions surrounding the spot mask. Median of pixel values in this region
Most software package implement such an approach
ScanAlyze ImaGene Spot, GenePix
By not considering the pixels immediately surrounding the spots, the background estimate is less sensitive to the performance of the segmentation procedure
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Constant background Global method which subtracts a
constant background for all spots Some findings suggests that the binding
of fluorescent dyes to ‘negative control spots’ is lower than the binding to the glass slide
-> More meaningful to estimate background based on a set of negative control spots If no negative control spots : approximation
of the average background = third percentile of all the spot foreground values
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No adjustment Do not consider the background
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References Yang, Y. H., Buckley, M. J., Dudoit, S. and
Speed, T. P. (2001), ‘Comparisons of methods for image analysis on cDNA microarray data’. Technical report #584, Department of Statistics, University of California, Berkeley.
Yang, Y. H., Buckley, M. J. and Speed, T. P. (2001), ‘Analysis of cDNA microarray images’. Briefings in bioinformatics, 2 (4), 341-349.
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Next time Data formats/files for Affymetrix
microarrays CEL and CDF
Intro to R Reading in microarray data Exploring array data
Assignment: For the gene, Pbx1, determine the probe design on either the mouse
Affymetrix 1.0 ST MoGene array or the Zebrafish genome array ? What is the difference between a probe and a probeset? You should be able to use resources at www.affymetrix.com but you
might need to register to get access to data files.
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For Pbx1,How many probes?What are the sequences of the probes?Where are the probes placed along the gene structure for Pbx1?
GoogleAffymetrix web site