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GeneChips and Microarray Expression Data

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Presentation on theme: "GeneChips and Microarray Expression Data"— Presentation transcript:

1 GeneChips and Microarray Expression Data
David Paoletti

2 The Problem Determine gene expression (activity)
What proteins are being produced by a group of cells?

3 The Assumption The RNA present in the cell determines what proteins are being produced Efficiency

4 The Why Understanding Toxicology Drug design Evaluation Specificity
Response

5 What is a GeneChip? 1.28 x 1.28 cm glass wafer  500,000 features
24 x 24 m probe site 25 mer oligo, complementary PM: perfect match MM: mismatch  2.5 M copies GeneChip

6 The Solution

7 The Gains Speed Possibility Sensitivity Reproducibility

8

9 The Process Poly-A RNA Biotin-labeled Antisense cRNA Cells cDNA IVT L
AAAA Fragment (heat, Mg2+) Labeled fragments Hybridize Wash/stain Scan L L L

10 Hybridization and Staining
GeneChip Biotin Labeled cRNA Hybridized Array L L L L + L L L + L L L L SAPE Streptavidin- phycoerythrin L

11 Specialized Equipment

12

13 How Features Are Chosen
5’ Gene Sequence 3’ Multiple oligo probes 25 mers Perfect Match Mismatch

14 Feature Values Remove outermost rows and columns
83 112 96 32 47 382 165 87 55 246 140 93 104 552 187 65 Remove outermost rows and columns Find 75th percentile of remaining values This value is taken as representative of this feature

15 Background Noise Removal
The array is divided into 16 equal sectors For each sector Find the lowest 2% of the feature intensities Average these Subtract this average from the intensity value of all features in the sector

16 Noise Calculation

17 Average Difference Intensity
For a given gene For each probe pair for the given gene Calculate the difference PM-MM Calculate ,  for this set If abs( (PM – MM) - )  3, delete from set Remaining set is pairs in avg

18 Positive & Negative Probe Pairs
PM-MM  SDT PM/MM  SRT MM-PM  SDT MM/PM  SRT If both true, mark as positive If both true, mark as negative SDT = Q · STDmult By default, SRT = 1.5, STDmult = 2.0 (low density), 4.0 (high)

19 Voting Methods for Absolute Call
Positive/negative ratio PNR = #pos / #neg Positive fraction PF = #pos / #used Log average ratio

20 Decision Matrix Absent Marginal Present PNR 3.00 4.00 PF 0.33 0.43 LA
0.90 1.30

21 Average Difference and Absolute Call
Which of these do you base a decision on, for whether a gene is being expressed? Use the absolute call for decision Use average difference to compare those which are present

22 Conclusions Incredible amalgam of biological and computational processes Allows analyses that would not be performed otherwise Already of proven worth

23 References Moore, S K; Making chips to probe genes, IEEE Spectrum, March 2001, GeneChip Gene Expression Algorithm Training, Part I: Absolute Analysis; Affymetrix. Berberich, S, and McGorry, M; GeneChip protocols; Wright State University.


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