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DNA Microarray Quality Control Carlo Colantuoni April 25, 2007
How many different ways can we look at global expression data?
Microarray Quality Control Depends on Technology
NHGRI Microarray Core Facility - Abdel Elkalhoun Oligonucleotide : 2-color Glass : Fluorescence : 36K
Illumina Microarray Platform Oligonucleotides : Beads : 24K : High Redundancy
Nylon NIA cDNA microarray Core Facility P MGC 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 Log Ratio
4 arrays: Raw Log Intensities
4 arrays: Raw Linear Intensities
1 array: Ratio v. Intensity
Bad Plate Effect
Print Order Effect
Uncorrected Intensities: MDS Colored by Batch
Removing The Batch Effect Much Like Red:Green Analysis
Uncorrected Intensities: MDS Colored by Batch
Batch Subtracted Measures: MDS Colored by Batch
MDS of All Array Experiments: Subject Replicates
Positive Controls in Microarray Quality Control
As Many Views As Possible: Combing many diverse data types/views to see effects Outliers Artifacts & Bias Positive Controls Dimension Reduction
NIMH Joel Kleinman Tom Hyde Danny Weinberger JHSPH Rafael Irizarry JHU Michela Gallagher NHGRI Abdel Elkalhoun NIA & NIDA Kevin Becker Bill Freed Elin Lehrman JMHI Akira Sawa
Artifacts and Effects in Gene Expression Data Carlo Colantuoni April 12, 2006.
Affymetrix vs. glass slide based arrays Affymetrix Short oligonucleotides Many oligos per gene Single sample hybridized to chip Fixed platform. Not universally.
Microarray hybridization Usually comparative – Ratio between two samples Examples – Tumor vs. normal tissue – Drug treatment vs. no treatment – Embryo.
Microarray Technology. Introduction Introduction –Microarrays are extremely powerful ways to analyze gene expression. –Using a microarray, it is possible.
Low-Level Analysis and QC Regional Biases Mark Reimers, NCI.
DNA Microarray Bioinformatics - #27612 Normalization Getting the numbers comparable.
Probes/Targets DNA Arrays...Probes: are the tethered nucleic acids with known sequence, –the DNA on the chip,...Target: is the free nucleic acid sample.
Idea: measure the amount of mRNA to see which genes are being expressed in (used by) the cell. Measuring protein might be more direct, but is currently.
Panu Somervuo, March 19, cDNA microarrays.
Microarray Quality Assessment Issues in High-Throughput Data Analysis BIOS Spring 2010 Dr Mark Reimers.
Introduce to Microarray. Copyright notice Many of the images in this power point presentation of other people. The Copyright belong to the original authors.
BiGCaT Bioinformatics Hunting strategy of the bigcat.
Microarray - Leukemia vs. normal GeneChip System.
Introduction to Microarray Gene Expression Shyamal D. Peddada Biostatistics Branch National Inst. Environmental Health Sciences (NIH) Research Triangle.
Summer Inst. Of Epidemiology and Biostatistics, 2008: Gene Expression Data Analysis 8:30am-12:30pm in Room W2017 Carlo Colantuoni –
Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data Rafael A. Irizarry Department of Biostatistics, JHU (joint.
Microarray technology and analysis of gene expression data Hillevi Lindroos.
MB Also known as DNA Chip Allows simultaneous measurement of the level of transcription for every gene in a genome (gene expression) Transcription?
Statistical Analysis for Expression Experiments Heather Adams BeeSpace Doctoral Forum Thursday May 21, 2009.
Gene Expression Data Qifang Xu. Outline cDNA Microarray Technology cDNA Microarray Technology Data Representation Data Representation Statistical Analysis.
Microarray Technology Types Normalization Microarray Technology Microarray: –New Technology (first paper: 1995) Allows study of thousands of genes at.
Experimental Design Reaching a balance between statistical power and available finances.
DNA Microarray: A Recombinant DNA Method. Basic Steps to Microarray: Obtain cells with genes that are needed for analysis. Isolate the mRNA using extraction.
What Is Microarray A new powerful technology for biological exploration Parallel High-throughput Large-scale Genomic scale.
Statistical Analyses of High Density Oligonucleotide Arrays Rafael A. Irizarry Department of Biostatistics, JHU (joint work with Bridget Hobbs and Terry.
ABC D EF GH I JKL. Supplementary figure S1: Exemplary overview of the quality assessment plots generated by Robin. All plots have been generated using.
Genomics I: The Transcriptome RNA Expression Analysis Determining genomewide RNA expression levels.
Henrik Bengtsson Mathematical Statistics Centre for Mathematical Sciences Lund University Plate Effects in cDNA Microarray Data.
DNA Microarray Overview and Application. Table of Contents Section One : Introduction Section Two : Microarray Technique Section Three : Types of DNA.
Introduction to Microarrays. The Central Dogma.
Gene Expression Data Analyses (2) Trupti Joshi Computer Science Department 317 Engineering Building North (O)
Microarray Data Analysis of Illumina Data Using R/Bioconductor Reddy Gali, Ph.D.
Microarrays: Basic Principle AGCCTAGCCT ACCGAACCGA GCGGAGCGGA CCGGACCGGA TCGGATCGGA Probe Targets Highly parallel molecular search and sort process based.
Jamie Mashek. What we will be discussing… What is DNA microarray? The purpose of using DNA microarray. The plate. Steps to perform a microarray.
Molecular Biology Dr. Chaim Wachtel April 4, 2013.
Probe-Level Data Normalisation: RMA and GC-RMA Sam Robson Images courtesy of Neil Ward, European Application Engineer, Agilent Technologies.
Distinguishing active from non active genes: Main principle: DNA hybridization -DNA hybridizes due to base pairing using H-bonds -A/T and C/G and A/U possible.
DNA Microarrays: An Introduction Jochen Mueller
Proteome and Gene Expression Analysis Chapter 15 & 16.
Microarray Data Analysis Data quality assessment and normalization for affymetrix chips.
Statistical Methods in Microarray Data Analysis Mark Reimers, Genomics and Bioinformatics, Karolinska Institute.
CISC667, F05, Lec24, Liao1 CISC 667 Intro to Bioinformatics (Fall 2005) DNA Microarray, 2d gel, MSMS, yeast 2-hybrid.
Summarization of Oligonucleotide Expression Arrays BIOS Winter 2010.
Model-based analysis of oligonucleotide arrays, dChip software Statistics and Genomics – Lecture 4 Department of Biostatistics Harvard School of Public.
Henrik Bengtsson Mathematical Statistics Centre for Mathematical Sciences Lund University, Sweden Plate Effects in cDNA Microarray Data.
DNA Microarray Bioinformatics - #27612 Normalization and Statistical Analysis.
1 Introduction to Oligonucleotide Microarray Technology 1/11/2011 Copyright © 2011 Dan Nettleton.
Microarray (Gene Expression) DNA microarrays is a technology that can be used to measure changes in expression levels or to detect SNiPs Microarrays differ.
Biology and Cells All living organisms consist of cells. Humans have trillions of cells. Yeast - one cell. Cells are of many different types (blood, skin,
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