Microarray Technology

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Microarray Technology

• Types
• Normalization

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Microarray Technology

• Microarray
• New Technology (first paper 1995)
• Allows study of thousands of genes at same time
• Glass slide of DNA molecules
• Molecule string of bases (25 bp 500 bp)
• uniquely identifies gene or unit to be studied

http//kbrin.a-bldg.louisville.edu/CECS694/
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Fabrications of Microarrays

• Size of a microscope slide

Images http//www.affymetrix.com/
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Differing Conditions

• Ultimate Goal
• Understand expression level of genes under
  different conditions
• Helps to
• Determine genes involved in a disease
• Pathways to a disease
• Used as a screening tool

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Gene Conditions

• Cell types (brain vs. liver)
• Developmental (fetal vs. adult)
• Response to stimulus
• Gene activity (wild vs. mutant)
• Disease states (healthy vs. diseased)

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Expressed Genes

• Genes under a given condition
• mRNA extracted from cells
• mRNA labeled
• Labeled mRNA is mRNA present in a given condition
• Labeled mRNA will hybridize (base pair) with
  corresponding sequence on slide

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Two Different Types of Microarrays

• Custom spotted arrays (up to 20,000 sequences)
• cDNA
• Oligonucleotide
• High-density (up to 100,000 sequences) synthetic
  oligonucleotide arrays
• Affymetrix (25 bases)
• SHOW AFFYMETRIX LAYOUT

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Custom Arrays

• Mostly cDNA arrays
• 2-dye (2-channel)
• RNA from two sources (cDNA created)
• Source 1 labeled with red dye
• Source 2 labeled with green dye

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Two Channel Microarrays

• Microarrays measure gene expression
• Two different samples
• Control (green label)
• Sample (red label)
• Both are washed over the microarray
• Hybridization occurs
• Each spot is one of 4 colors

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(Slide source http//www.bsi.vt.edu/)
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Microarray Image Analysis

• Microarrays detect gene interactions 4 colors
• Green high control
• Red High sample
• Yellow Equal
• Black None
• Problem is to quantify image signals

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Information Extraction

• Spot Intensities
• mean (pixel intensities).
• median (pixel intensities).
• Background values
• Local
• Morphological opening
• Constant (global)
• None
• Quality Information

Take the average
Background
Signal
Speed Group Microarray Page http//stat-www.berkel
ey.edu/users/terry/zarray/Html/image.html
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Single Color Microarrays

• Prefabricated
• Affymetrix (25mers)
• Custom
• cDNA (500 bases or so)
• Spotted oligos (70-80 bases)

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Single Color Microarrays

• Expressed sequences washed over chips
• Expressed genes hybridize
• Light passed under to see intensity (or
  hybridized oligos show dark color)

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Single Color Microarrays
Image http//www4.nationalacademies.org/
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Affymetrix Technology
DESOKY, 2003
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Affymetrix Technology
DESOKY, 2003
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Lithography

• It is a printing technology.
• Lithography was invented by Alois Senefelder in
  Germany in 1798.
• The printing and non-printing areas of the plate
  are all at the same level, as opposed to intaglio
  and relief processes in which the design is cut
  into the printing block.
• Lithography is based on the chemical repellence
  of oil and water.

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Lithography

• Designs are drawn or painted with greasy ink or
  crayons on specially prepared limestone. The
  stone is moistened with water, which the stone
  accepts in areas not covered by the crayon. An
  oily ink, applied with a roller, adheres only to
  the drawing and is repelled by the wet parts of
  the stone. The print is then made by pressing
  paper against the inked drawing.

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Affymetrix Array Construction
STROMBERG, 2003
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Affymetrix Technology

• Biotin (one dye) instead of 2 colors
• One treatment per chip
• 11, 16, or 20 gene markers pairs per gene

DESOKY, 2003
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Affymetrix Data

• Each gene labeled as present, marginal, or
  absent.
• Present gene expressed and reliably detected in
  the RNA sample
• Label chosen based on a p-value

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Affymetrix Design of probes

• PM to maximize hybridization
• MM to ascertain the degree of
  cross-hybridization

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STROMBERG, 2003
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Inferential statistics
Paradigm Parametric test Nonparametric Compare
two unpaired groups Unpaired t-test Mann-Whitney
test Compare two paired groups Paired
t-test Wilcoxon test Compare 3 or ANOVA more
groups
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Inferential statistics
Is it appropriate to set the significance level
to p lt 0.05? If you hypothesize that a specific
gene is up-regulated, you can set the probability
value to 0.05. You might measure the expression
of 10,000 genes and hope that any of them are up-
or down-regulated. But you can expect to see 5
(500 genes) regulated at the p lt 0.05 level by
chance alone. To account for the thousands of
repeated measurements you are making, some
researchers apply a Bonferroni correction. The
level for statistical significance is divided by
the number of measurements, e.g. the criterion
becomes p lt (0.05)/10,000 or p lt 5 x 10-6
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Data matrix (20 genes and 3 time points from Chu
et al.)