1. Microarray Data Analysis Day 2

2. Microarray Data Process/Outline
Experimental Design
Image Analysis – scan to intensity measures (raw data)
Normalization – “clean” data
More “low level” analysis-fold change, ANOVA, (Z-score) --data filtering
Data mining-how to interpret > 6000 measures
Databases
Software
Techniques-clustering, pattern recognition etc.
Comparing to prior studies, across platforms?
Validation *

3. Today we will be using Spotfire software to filter and search your data records in Spotfire S. pombe specific Affy controls S. cerevisiae specific

4. 6603
4377
1407
819
The Affy detection oligonucleotide sequences are frozen at the time of synthesis, how does this impact downstream data analysis?

5. Biology and Data Mining

6. Subcellular Localization, Provides a simple goal for genome-scale functional prediction
Determine how many of the ~6000 yeast proteins go into each compartment

7. Subcellular Localization, a standardized aspect of function
Cytoplasm
Nucleus
Membrane ER
Extra- cellular [secreted]
Golgi
Mitochondria

8. "Traditionally" subcellular localization is "predicted" by sequence patterns
Cytoplasm
NLS
Nucleus
Membrane
TM-helix ER
HDEL
Extra- cellular [secreted]
Golgi
Import Sig.
Mitochondria
Sig. Seq.

9. [Expression Level in Copies/Cell]
Subcellular localization is associated with the level of gene expression
[Expression Level in Copies/Cell]
Cytoplasm
Nucleus
Membrane ER
Extra- cellular [secreted]
Golgi
Mitochondria

10. [Expression Level in Copies/Cell]
Combine Expression Information & Sequence Patterns to Predict Localization
[Expression Level in Copies/Cell]
Cytoplasm
NLS
Nucleus
Membrane
TM-helix ER
HDEL
Extra- cellular [secreted]
Golgi
Import Sig.
Mitochondria
Sig. Seq.

11. The central dogma of molecular biology???
Major Objective: Discover a comprehensive theory of life’s organization at the molecular level
The major actors of molecular biology: the nucleic acids, DeoxyriboNucleic Acid (DNA) and RiboNucleic Acids (RNA)
The central dogma of molecular biology???
Epigenetics
RNA editing
Post-translational modification
Translational regulation
Proteins are very complicated molecules with 20 different amino acids.

12. Biology Application Domain
Validation
Data Analysis
Microarray Experiment
Image Analysis
Data Mining
Experiment
Design and
Hypothesis
Data Warehouse
Artificial Intelligence (AI)
Knowledge discovery in databases (KDD)
Statistics

13. Higher Level Microarray data analysis
Clustering and pattern detection
Data mining and visualization
Linkage between gene expression data and gene sequence/function/metabolic pathways databases
Discovery of common sequences in co-regulated genes
Meta-studies using data from multiple experiments

14. Scatter plot of all genes in a simple comparison of two control (A) and two treatments (B: high vs. low glucose) showing changes in expression greater than 2.2 and 3 fold.

15. Types of Clustering Herarchical Self Organizing Maps (SOM)
Link similar genes, build up to a tree of all
Self Organizing Maps (SOM)
Split all genes into similar sub-groups
Finds its own groups (machine learning)

16. Cluster by color/expression difference

17. Self Organizing Maps

18. Public Databases
Gene Expression data is an essential aspect of annotating the genome
Publication and data exchange for microarray experiments
Data mining/Meta-studies
Common data format - XML
MIAME (Minimal Information About a Microarray Experiment)

19. The 3 Gene Ontologies Molecular Function = elemental activity/task
the tasks performed by individual gene products; examples are carbohydrate binding and ATPase activity
Biological Process = biological goal or objective
broad biological goals, such as mitosis or purine metabolism, that are accomplished by ordered assemblies of molecular functions
Cellular Component = location or complex
subcellular structures, locations, and macromolecular complexes; examples include nucleus, telomere, and RNA polymerase II holoenzyme

20. One Last Note Microarrays are “cutting edge” technology
You now have experience doing a technique that most Ph.D.s have never done
Looks great on a resume…