1. Microarray Dataset: quick mining
and gene profile analysis using
online tools
Dr. Etienne Z. GNIMPIEBA
Sioux Falls, March 2013
Etienne.gnimpieba@usd.edu

2. Plan
 Gene expression measurement
 Microarray process
 Gene expression data stores
 Data mining / quering
 Data analysis
 Example: ATP13A2 profile in stress
conditions

3. Gene expression
measurement
Higher-plex techniques:
SAGE
DNA microarray
Tiling array
RNA-Seq
NGS
Low-to-mid-plex techniques:
Reporter gene
Northern blot
Western blot
Fluorescent in situ
hybridization
Reverse transcription PCR

4. What is a Microarray?
“A DNA microarray is a multiplex technology
consisting of thousands of oligonucleotide
spots, each containing picomoles of a
specific DNA sequence.”
 Used to quantitate mRNA or DNA
 Many applications:
◦ mRNA or DNA levels
◦ SNP identification
◦ ChIP-on-Chip

5. Hypotheses
 Microarrays are usually hypothesis-generating:
◦ They highlight specific genes or features that are
particularly interesting for follow-up experiments
◦ There are many interesting exceptions
 Biomarkers
 Pathway analyses
 This does not reduce the importance of
experimental design
◦ the low statistical power of array studies make good
design even more important and very challenging

6. Microarray process (1/3)
• Image analysis
(genepix)
• Normalization (R)
• Pre-treatment
• Differential expression
• Clustering
• Data mining
• Annotation

7. Microarray process (2/3)

8. Microarray process (3/3)
High density
filters(macroarrays)
Glass slides
(microarrays)
Oligonucleotides
chips
Detail: Detail: Detail:
Size: 12cm x 8cm Size: 5,4cm x 0,9cm Size: 1,28cm x 1,28cm
•2400 clones by
membrane
•radioactive labelling
•1 experimental
condition by membrane
•10000 clones by slide
•fluorescent labelling
•2 experimental
conditions by slide
•300000
oligonucleotides by
slide
•fluorescent labelling
•1 experimental
condition by slide

9. Gene expression data
management
Database
Microarray
Experiment
Sets
Sample
Profiles
Date Reported
ArrayExpress at EBI 24,838 708,914 October 28, 2011
ArrayTrack™ 1,622 50,953 February 11, 2012
caArray at NCI 41 1,741 November 15, 2006
Gene Expression Omnibus -
NCBI
25,859 641,770 October 28, 2011
Genevestigator database 2,500 65,000 January 2012
MUSC database ~45 555 April 1, 2007
Stanford Microarray database 82,542 Not reported October 23, 2011
UNC Microarray database ~31 2,093 April 1, 2007
UNC modENCODE Microarray
database
~6 180 July 17, 2009
UPenn RAD database ~100 ~2,500 September 1, 2007
UPSC-BASE ~100 Not reported November 15, 2007
SAGE
GEO
GUDMAP (421)
MGI
BIOGPS

10. Data mining / querying
 Problem specification
 Query
 Extraction
 Storage
 Load
 Pretreat / prepare for analysis

11. Data analysis (1/3)
 Question-Answer
◦ Experimental condition profile: group
comparison
◦ Annotation profile: systems biological involved
◦ Clustering profile: co-regulation
◦ Time course profile: time variation
◦ …
 Descriptive
◦ Boxplot (SD, MEAN, MEDIAN, )
◦ Scatter plot
 Predictive / inference (clustering)
 Modeling (machine learning, simulation)

12. Data analysis (2/3)
 3 Questions
◦ What is the right dataset (experimental condition)?
◦ Is dataset is ready for analysis (quality)?
◦ What is the expression profile for a given gene?
◦ Significant differential expression in groups
comparison
 Tools
◦ ArrayExpress (EBI)
◦ Boxplot
◦ GEO2R (LIMMA, profile graph,)
◦ ….

13. Data analysis (3/3)
Boxplot

14. Example: ATP13A2 profile in stress
conditions
 Specification: ATP13A2 profile in
stress conditions
 Data querying:
◦ GEO
◦ Array Express
◦ Gene Atlas
 Data analysis:
◦ Online: GEO2R, Genospace, …
◦ Desktop: R, ArrayTrack, …

15. Significant differential expression
!!!
Kerry Bemis slides