Quantitative Methods to Analyze cDNA Microarray Data.ppt

Quantitative Methods to Analyze cDNA Microarray Data
Peter von Rohr
Department of Animal Sciences, Animal Breeding
ETH-Zentrum, CLU C4,
CH-8092 Zurich
peter.******@
Acknowledgments
Virginia Tech
Dairy Science and Statistics
Ina Hoeschele
Fengxing Du
David Henderson
Plant Pathology
Ruth Alscher
Verlin Strandberg
Forest Biotechnology Group
Ying-Hsuan Sun
Ross Whetten
Ron Sederoff
NC State
NIH
NHGRI
Yidong Chen
Mike Bittner
Overview
Experiment

Data

Methods

The End
Drought stress in loblolly pine
- Image Analysis
- Description
- Basic statistical analysis
- Cluster analysis
- Pattern recognition
- Software
- Summary
mild stress
no stress
Experiment
Drought stress in loblolly pine
3 levels of drought stress
no stress
mild stress
no stress
severe stress
mild stress
severe stress
control
probe
red
green
red
green
label
scanner
Image Analysis
2 images per array
Super-imposing
Grid on image
Data Description
Ratios, why?
Gene expression levels determined by intrinsic properties of each gene
low
high
expression level
Gene A
Gene B


Statistical Analysis
Differences in ratios due to
random variation
meaningful changes
Hypothesis testing, with
H0: no systematic differences between ratios
pdf under H0
Statistical Analysis
Assumptions
‘red’ and ‘green’ intensities at a given gene
~ mon variance
constant coefficient of variation over the whole gene set
approximation due to highly positive value assumption of intensities
Statistical Analysis
with Tk = Rk / Gk ,
with c: coefficient of variation, estimated from data
According to Chen et al. 1997 (J Biomedical Optics, 2(4):364)
Statistical Analysis
Classification with hypothesis testing
under-expressed
over-expressed
/2
/2
3 classes of genes