Data Mining of GeneChips_ppt.ppt

Data Mining of GeneChips®
Devang Shah
INT3470 Course Project
March 14, 2002
Outline
Background
Molecular Biology 101
GeneChip® Technology
Synthesis, Sample Preparation, Scanning
Data Flow and Management
Multidrug Resistance
Preliminary Data Analysis
Affymetrix Microarray Suite
Scoring posite Analysis
Statistical Algorithms (parison Analysis)
Data Mining Tool (Preview)
SOM Algorithm
Correlation Coefficient Clustering
Molecular Biology 101
A -> T
G -> C
Traditional methods result in “one gene at one time” analysis
The need for higher throughput has led to the development of two (competing) technologies
cDNA Spotted Array
cDNA Microarrays utilize various technologies (spotting, piezoelectric, drop-touch) to create arrays of entire genomes using 500-5000 bp oligos representing entire genes
Microarrays are scanned using laser microscopy with fluorescent labeled DNA
GeneChip® Technology
Utilizes photolithography binatorial chemistry to synthesize microarrays consisting of ~25mer oligos representing smaller regions of various genes
Probe Cell (PM or MM)
Probe Pair (PM + MM)
Probe Set ( ~18 Pairs)
Typical experiment involves isolation of mRNA, synthesis of cDNA, fragmentation, labeling , and hybridization
Scan results in a raw data file (*.CHP)
Data Management
Nat 1999 Jan;21(1 Suppl):51-5 Gene expression informatics--it's all in your mine. Bassett DE Jr, Eisen MB, Boguski MS
Use in Functional Genomics
Antimicrobial resistance in bacteria
Multi-drug pumps (MDR’s)
Facilitate extrusion of amphipathic cations (toxic)
TolC (E. coli), NorA (S. aureus)
Evolutionary paradigm:
Why do plants continue to produce pounds if they are extruded???
Perhaps they produce MDR inhibitors that bined with these normally ineffective antimicrobials provide a strong synergistic effect
Methods
E. coli TolC mutants were challenged with pounds for several hours and then assayed for gene expression
S. aureus (WT + NorA Mutant) susceptibility to various plant pounds were test