dna microarray quality control carlo colantuoni [email protected] april 25, 2007
TRANSCRIPT
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How many different ways can we look at
global expression data?
Microarray Quality Control Depends on
Technology
NHGRI Microarray Core Facility - Abdel ElkalhounOligonucleotide : 2-color Glass : Fluorescence : 36K
Illumina Microarray PlatformOligonucleotides : Beads : 24K : High Redundancy
Nylon
NIA cDNA microarray Core Facility
P33
9600MGC
elements
Affymetrix - short oligos : many 10,000’s
Outlier Identification in Microarray Quality
Control
Microarray Pseudo Images: Intensity
Microarray Pseudo Images: Ratios
Images of probe level data
This is the raw data
Images of probe level data
Residuals (or weights) from probe level model fits show problem clearly
Artifact & Bias Removal in Microarray Quality
Control
Intensities and Ratios
Green
Red
Intensity
Lo
g R
atio
4 arrays: Raw Log Intensities
4 arrays: Raw Linear Intensities
1 array: Ratio v. Intensity
Print-tip Effect
Bad Plate Effect
Bad Plate Effect
Print Order Effect
Uncorrected Intensities: MDS Colored by Batch
Removing The Batch Effect
Much LikeRed:Green Analysis
Uncorrected Intensities: MDS Colored by Batch
Batch Subtracted Measures: MDS Colored by Batch
MDS of All Array Experiments: Subject Replicates
Hybridization Artifacts
AGE
?
AGE
RN
A Q
ual
ity
AGE
Bat
ch
Positive Controlsin Microarray Quality
Control
As Many Views As Possible: Combing many diverse data types/views to see effects
OutliersArtifacts & Bias
Positive Controls
Dimension Reduction
NIMHJoel Kleinman
Tom HydeDanny Weinberger
JHSPHRafael Irizarry
JHUMichela Gallagher
NHGRIAbdel Elkalhoun
NIA & NIDAKevin Becker
Bill FreedElin Lehrman
JMHIAkira Sawa
