DNA Microarray Market Trends (Installed Base, Applications, Purchase Plans and The Impact of Next-Gen Sequencing)
DNA Microarrays are utilized heavily by research labs for a number of tasks such as gene profiling, RNA detection and SNP analysis. But as Kalorama Information's DNA Market Trends report indicates, the market for these systems is about to experience change. The report authored by Kalorama Information biotech analyst Justin Saeks, is the result of surveys carried out with microarray labs to determine the current state of the microarray market and attempt to predict the future direction of the technologies.
As part of the survey , analyst Justin Saeks contacted 114 labs worldwide (76% U.S.) to determine the current usage of the DNA microarrays, system installs and future purchases, as well as where they will intersect with next-generation sequencing. The following represents the types of data the survey addressed and this report provides:
Respondents were asked what type of brands they use or plan to use, types of applications run most commonly with each brand, and their future purchase plans. Products of the following companies are among the survey results in this report:
As part of the survey , analyst Justin Saeks contacted 114 labs worldwide (76% U.S.) to determine the current usage of the DNA microarrays, system installs and future purchases, as well as where they will intersect with next-generation sequencing. The following represents the types of data the survey addressed and this report provides:
- Number and brand of Microarry systems owned
- Fluidics stations and/ or Hybridization Ovens Used
- Applications Run Most Often
- Chips Run Most, Samples Run Per Month
- Catalog Arrays versus Commercial or In-house Custom Arrays
- Outsourcing of Microarray Samples
- What Microarray Features, or Steps in the Sequencing Process Labs Would Like to Change
- Main Bottlenecks in Microarray Process
- Lab-Identified Challenges of Data Analysis and Data Management
- Applications with an Increase in Samples from 2011 - 2013?
- How Labs expect Next-generation Sequencing to Affect the Usage of Microarrays
- Sample Preparation Products Used
- Future Purchase Plans and Time-Frames
Respondents were asked what type of brands they use or plan to use, types of applications run most commonly with each brand, and their future purchase plans. Products of the following companies are among the survey results in this report:
- Affymetrix
- Molecular Devices/ Axon
- Agilent
- Illumina
- NimbleGen
- PerkinElmer
- ND
- Agilent
- NimbleGen/ MAUI
- Advalytics
- Digilab
- SciGene HyBex
- BioConductor
- Partek
- GeneSpring
- GeneSifter
- In-house
- Array-Pro Analyzer
- ArrayStar
- Biominer
- Chipster
- GeneDirector
- GenePix Pro
- Rosetta Resolver
- Dchip
- GMP Genomics
- Ingenuity
- Pacific Biosciences
- Ion Torrent
- ABI
- Roche/454
CHAPTER ONE: EXECUTIVE SUMMARY
Introduction
Scope
Lab Demographics
Summary of Findings
CHAPTER TWO: INTRODUCTION & DEMOGRAPHICS
Methodology
Outline
Demographics
Regional Distribution of Respondents’ Labs
Industrial Distribution of Respondents Labs
Laboratory Function of Respondents’ Labs
Overall
Regional Distribution
Positions/ Titles of Respondents
Distribution of Systems Installed
Numbers of Scanners/ Readers in Labs
Numbers of Fluidics Stations
Numbers of Hybridization Ovens
Number of Other Scanners/ Readers in Organization
Number of Other Scanners/ Readers in Organization
Brand(s) of Scanners/ Readers Owned
CHAPTER THREE: SYSTEM INSTALLATIONS
Distribution of Scanner Models
Total and Average Number of Readers by Brand
Affymetrix Scanners/ Readers Installed
Illumina Scanners/ Readers Installed
Agilent Scanners/ Readers Installed
Molecular Devices (Axon) Readers/ Scanners Installed
Other Scanners/ Readers Installed
Brands of Scanners in Labs, Cross-Referenced
Brands of Hybridization Ovens
3rd Party Software Used for Data Analysis
Installed Base by Region
Overall Brand/ Type
Installed Base of Readers by Industry Segment
Installed Base of Readers by Laboratory Function
Applications and Usage Trends
Applications, Chips, Number of Samples
Applications Run Overall and by Brand/ Type
Applications Most Likely to Increase
Number of Microarray Samples Run per Month, by Brand
Brand of Microarrays Used Most by Scanner/ Reader
Top Catalog Microarray Products Used, by Brand
Usage of Catalog vs Custom Chips
Main Source for Custom Microarrays/ Probes
Outsourcing
Systems Used to Check Concentration, Size, Quality
CHAPTER FOUR: PREFERENCES AND EVALUATIONS
Ratings and Evaluations of Systems
Ratings by Brand
End-user Verbatim Comments About Microarray System Brands
General (multiple brands)
Affymetrix
Agilent
Illumina
In-house/ spotted
NimbleGen
Changes or Improvements, by Brand
Bottlenecks in Process, by Brand
Criteria for Choosing Sample Preparation Products
Brands Used Most for Sample Preparation
RNA/DNA Extraction
Brands Used for Amplification and Labeling
Difficulty of Data Analysis & Data Management
Data Analysis
Data Management
End-User Verbatim Comments
Data Analysis
CHAPTER FIVE: FUTURE PURCHASE PLANS
Time-Frame of Microarray System Purchase Plans
System Purchases Planned Within Two Years
Systems Labs Would Choose Today for Same Applications
Expected Effects of Next-Gen Sequencing on Microarrays
Impact of Sequencing on Labs’ Microarray Usage
End-User Verbatim Comments
Near-term Effects, Large Effects
Longer term Effects
Minor effects
Introduction
Scope
Lab Demographics
Summary of Findings
CHAPTER TWO: INTRODUCTION & DEMOGRAPHICS
Methodology
Outline
Demographics
Regional Distribution of Respondents’ Labs
Industrial Distribution of Respondents Labs
Laboratory Function of Respondents’ Labs
Overall
Regional Distribution
Positions/ Titles of Respondents
Distribution of Systems Installed
Numbers of Scanners/ Readers in Labs
Numbers of Fluidics Stations
Numbers of Hybridization Ovens
Number of Other Scanners/ Readers in Organization
Number of Other Scanners/ Readers in Organization
Brand(s) of Scanners/ Readers Owned
CHAPTER THREE: SYSTEM INSTALLATIONS
Distribution of Scanner Models
Total and Average Number of Readers by Brand
Affymetrix Scanners/ Readers Installed
Illumina Scanners/ Readers Installed
Agilent Scanners/ Readers Installed
Molecular Devices (Axon) Readers/ Scanners Installed
Other Scanners/ Readers Installed
Brands of Scanners in Labs, Cross-Referenced
Brands of Hybridization Ovens
3rd Party Software Used for Data Analysis
Installed Base by Region
Overall Brand/ Type
Installed Base of Readers by Industry Segment
Installed Base of Readers by Laboratory Function
Applications and Usage Trends
Applications, Chips, Number of Samples
Applications Run Overall and by Brand/ Type
Applications Most Likely to Increase
Number of Microarray Samples Run per Month, by Brand
Brand of Microarrays Used Most by Scanner/ Reader
Top Catalog Microarray Products Used, by Brand
Usage of Catalog vs Custom Chips
Main Source for Custom Microarrays/ Probes
Outsourcing
Systems Used to Check Concentration, Size, Quality
CHAPTER FOUR: PREFERENCES AND EVALUATIONS
Ratings and Evaluations of Systems
Ratings by Brand
End-user Verbatim Comments About Microarray System Brands
General (multiple brands)
Affymetrix
Agilent
Illumina
In-house/ spotted
NimbleGen
Changes or Improvements, by Brand
Bottlenecks in Process, by Brand
Criteria for Choosing Sample Preparation Products
Brands Used Most for Sample Preparation
RNA/DNA Extraction
Brands Used for Amplification and Labeling
Difficulty of Data Analysis & Data Management
Data Analysis
Data Management
End-User Verbatim Comments
Data Analysis
CHAPTER FIVE: FUTURE PURCHASE PLANS
Time-Frame of Microarray System Purchase Plans
System Purchases Planned Within Two Years
Systems Labs Would Choose Today for Same Applications
Expected Effects of Next-Gen Sequencing on Microarrays
Impact of Sequencing on Labs’ Microarray Usage
End-User Verbatim Comments
Near-term Effects, Large Effects
Longer term Effects
Minor effects
TABLE OF EXHIBITS
CHAPTER ONE: EXECUTIVE SUMMARY
Table 1-1: Summary of Findings
CHAPTER TWO: INTRODUCTION & DEMOGRAPHICS
Table 2-1: Regional Distribution of Respondent Labs
Figure 2-1: Regional Distribution of Respondent Labs
Table 2-2: Industrial Distribution of Respondent Labs
Figure 2-2: Industrial Distribution of Respondent Labs
Table 2-3: Industrial Distribution by Region
Table 2-4: Industrial Distribution by Region
Figure 2-3: Industrial Distribution by Region
Table 2-5: Distribution of Labs’ Main Function(s)
Figure 2-4: Distribution of Labs’ Main Function(s)
Table 2-6: Distribution of Lab Function(s) by Region
Table 2-7: Distribution of Lab Function(s) by Region
Figure 2-5: Distribution of Lab Function(s) by Region
Table 2-9: Distribution of Respondents’ Position/ Title
Figure 2-6: Distribution of Respondents’ Position/ Title
Table 2-10: Distribution of Total Number of Scanners/ Readers
Figure 2-7: Distribution of Total Number of Scanners/ Readers
Table 2-11: Distribution of Number of Affymetrix Fluidics Stations
Figure 2-8: Distribution of Number of Affymetrix Fluidics Stations
Table 2-12: Distribution of Number of Hybridization Ovens
Table 2-13: Number of Other Scanners/ Readers in Organization
Table 2-14: Other Systems Used in Lab for These Applications
Figure 2-9: Other Systems Used in Lab for These Applications
Table 2-15: Brand(s) of Scanner/ Reader Owned
Figure 2-10: Brand(s) of Scanner/ Reader Owned
CHAPTER THREE: SYSTEM INSTALLATIONS
Table 3-1: Number of Systems Installed, by Brand
Figure 3-1: Average Number of Systems Installed, by Brand
Table 3-2: Scanner Models Installed in Affymetrix Owning Labs
Figure 3-2: Scanner Models in Affymetrix Owning Labs (% of Sys)
Table 3-4: System Models Installed in Illumina Owning Labs
Figure 3-4: System Models Installed in Illumina Owning Labs (% of Sys)
Table 3-5: Scanner Models Installed in Agilent Owning Labs
Figure 3-5: Scanner Models Installed in Agilent Owning Labs (% of Sys)
Table 3-6: Scanner Models Installed in Molec. Devices Owning Labs
Figure 3-6: Scanners Installed in Molec. Devices Owning Labs (% of Sys)
Table 3-7: Other Scanners Installed in Respondent Labs
Figure 3-7: Other Scanners Installed in Respondent Labs (% of Systems)
Table 3-8: Brands of Readers in Labs Owning Given Brand (# of Systems)
Figure 3-8: Brands of Readers in Labs Owning Given Brand (% of Systems)
Table 3-9: Brands of Hybridization Ovens Installed
Figure 3-9: Brands of Hybridization Ovens Installed (% of Systems)
Table 3-10: Third-Party Software Used for Data Analysis
Table 3-11: Number of Scanners/ Readers by Region
Table 3-12: Brands of Scanners/ Readers by Region
Table 3-13: Brands of Scanners/ Readers by Region
Figure 3-10: Brands of Scanners/ Readers by Region (% of Systems)
Table 3-14: Regional Distribution Cross-Referenced by Brand
Table 3-15: Number of Scanners/ Readers by Industry/ Segment
Table 3-16: Brands of Scanners/ Readers by Industry/ Segment
Table 3-17: Brands of Scanners/ Readers by Industry/ Segment
Table 3-18: Industrial Distribution Cross-Referenced by Brand
Table 3-19: Number of Scanners/ Readers by Lab Function
Table 3-20: Brands of Scanners/ Readers by Lab Function
Table 3-21: Brands of Scanners/ Readers by Lab Function
Table 3-22: Lab Function Distribution, Cross-Referenced by Brand
Table 3-23: Applications Run on System, by Brand of Reader
Figure 3-11: Applications Run on System, by Brand of Reader
Table 3-24: Applications Most Likely to Increase
Figure 3-12: Applications Most Likely to Increase
Table 3-25: Number of Samples/ Month, by Brand (# of Scanners)
Table 3-26: Number of Samples/ Month, by Brand (% of Scanners)
Table 3-27: # Samples/ Month by Brand, Cross-Referenced by # Samples
Table 3-26: Microarray Brand(s) Used Most by Reader (# of Readers)
Table 3-27: Microarray Brand(s) Used Most by Reader (% of Readers)
Table 3-28: Brands Used by Reader, Cross-Referenced by Chip Brand
Table 3-29: Top Three Microarrays Used, by Brand
Table 3-30: Percentage Usage of Catalog vs Custom Chips
Figure 3-13: Percentage Usage of Catalog vs Custom Chips
Table 3-31: Source(s) of Custom Microarrays/ Probes (% of Labs)
Figure 3-14: Source(s) of Custom Microarrays/ Probes (% of Labs)
Table 3-32: Outsourcing of Microarray Samples
Figure 3-15: Outsourcing of Microarray Samples
Table 3-33: Reasons for Outsourcing Microarray Samples
Figure 3-16: Reasons for Outsourcing Microarray Samples
Table 3-34: Systems Used to Check Concentration, Size, Quality
Figure 3-17: Systems Used to Check Concentration, Size, Quality
CHAPTER FOUR: PREFERENCES AND EVALUATIONS
Table 4-1: Microarray Systems Ratings, by Major Brands (Cost, Throughput, Software, Dynamic Range, Ease of Use, Content on Arrays, Sample Size, Customer Service)
Figure 4-1: Microarray Systems Ratings, by Brand (Cost, Throughput, Software, Dynamic Range, Ease of Use, Content on Arrays, Sample Size, Customer Service)
Table 4-2: Features/ Steps to Improve or Change, by Brand
Table 4-3: Features/ Steps to Improve or Change, by Brand
Table 4-4: Bottleneck Where Samples Back Up, by Brand(Sample Prep, Fluidics, Labeling, Scanning, Data Analysis, Personnel, Hybridization, Other )
Table 4-5: Bottleneck Where Samples Back Up, by Brand (Sample Prep, Fluidics, Labeling, Scanning, Data Analysis, Personnel, Hybridization, Other )
Table 4-6: Criteria for Choosing Sample Preparation Products (Precedence, Cost, Ease of Use, Reproducibility, Throughput, Automation, Small Sample, Customer Service, Other)
Figure 4-2: Criteria for Choosing Sample Preparation Products (Precedence, Cost, Ease of Use, Reproducibility, Throughput, Automation, Small Sample, Customer Service, Other)
Table 4-7: Brands Used Most for RNA/ DNA Extraction
Figure 4-3: Brands Used Most for RNA/ DNA Extraction
Table 4-8: Brands Used Most for Amplification and Labeling
Figure 4-4: Brands Used Most for Amplification and Labeling
Table 4-9: Difficulty of Data Analysis
Figure 4-5: Difficulty of Data Analysis
Table 4-10: Difficult of Data Management
Figure 4-6: Difficulty of Data Management
CHAPTER FIVE: FUTURE PURCHASE PLANS
Table 5-1: Planned Purchases of Systems Within Two Years
Figure 5-1: Planned Purchases of Systems Within Two Years
Table 5-2: Time-Frame of Purchase Plans Within Two Years
Figure 5-2: Time-Frame of Purchase Plans Within Two Years
Table 5-3: Brands of Planned System Purchases
Figure 5-3: Brands of Planned System Purchases
Table 5-4: System(s) Labs Would Choose Today for Same Applications
Figure 5-4: System(s) Labs Would Choose Today for Same Applications
Table 5-5: Impact of Next-Gen Sequencing
CHAPTER ONE: EXECUTIVE SUMMARY
Table 1-1: Summary of Findings
CHAPTER TWO: INTRODUCTION & DEMOGRAPHICS
Table 2-1: Regional Distribution of Respondent Labs
Figure 2-1: Regional Distribution of Respondent Labs
Table 2-2: Industrial Distribution of Respondent Labs
Figure 2-2: Industrial Distribution of Respondent Labs
Table 2-3: Industrial Distribution by Region
Table 2-4: Industrial Distribution by Region
Figure 2-3: Industrial Distribution by Region
Table 2-5: Distribution of Labs’ Main Function(s)
Figure 2-4: Distribution of Labs’ Main Function(s)
Table 2-6: Distribution of Lab Function(s) by Region
Table 2-7: Distribution of Lab Function(s) by Region
Figure 2-5: Distribution of Lab Function(s) by Region
Table 2-9: Distribution of Respondents’ Position/ Title
Figure 2-6: Distribution of Respondents’ Position/ Title
Table 2-10: Distribution of Total Number of Scanners/ Readers
Figure 2-7: Distribution of Total Number of Scanners/ Readers
Table 2-11: Distribution of Number of Affymetrix Fluidics Stations
Figure 2-8: Distribution of Number of Affymetrix Fluidics Stations
Table 2-12: Distribution of Number of Hybridization Ovens
Table 2-13: Number of Other Scanners/ Readers in Organization
Table 2-14: Other Systems Used in Lab for These Applications
Figure 2-9: Other Systems Used in Lab for These Applications
Table 2-15: Brand(s) of Scanner/ Reader Owned
Figure 2-10: Brand(s) of Scanner/ Reader Owned
CHAPTER THREE: SYSTEM INSTALLATIONS
Table 3-1: Number of Systems Installed, by Brand
Figure 3-1: Average Number of Systems Installed, by Brand
Table 3-2: Scanner Models Installed in Affymetrix Owning Labs
Figure 3-2: Scanner Models in Affymetrix Owning Labs (% of Sys)
Table 3-4: System Models Installed in Illumina Owning Labs
Figure 3-4: System Models Installed in Illumina Owning Labs (% of Sys)
Table 3-5: Scanner Models Installed in Agilent Owning Labs
Figure 3-5: Scanner Models Installed in Agilent Owning Labs (% of Sys)
Table 3-6: Scanner Models Installed in Molec. Devices Owning Labs
Figure 3-6: Scanners Installed in Molec. Devices Owning Labs (% of Sys)
Table 3-7: Other Scanners Installed in Respondent Labs
Figure 3-7: Other Scanners Installed in Respondent Labs (% of Systems)
Table 3-8: Brands of Readers in Labs Owning Given Brand (# of Systems)
Figure 3-8: Brands of Readers in Labs Owning Given Brand (% of Systems)
Table 3-9: Brands of Hybridization Ovens Installed
Figure 3-9: Brands of Hybridization Ovens Installed (% of Systems)
Table 3-10: Third-Party Software Used for Data Analysis
Table 3-11: Number of Scanners/ Readers by Region
Table 3-12: Brands of Scanners/ Readers by Region
Table 3-13: Brands of Scanners/ Readers by Region
Figure 3-10: Brands of Scanners/ Readers by Region (% of Systems)
Table 3-14: Regional Distribution Cross-Referenced by Brand
Table 3-15: Number of Scanners/ Readers by Industry/ Segment
Table 3-16: Brands of Scanners/ Readers by Industry/ Segment
Table 3-17: Brands of Scanners/ Readers by Industry/ Segment
Table 3-18: Industrial Distribution Cross-Referenced by Brand
Table 3-19: Number of Scanners/ Readers by Lab Function
Table 3-20: Brands of Scanners/ Readers by Lab Function
Table 3-21: Brands of Scanners/ Readers by Lab Function
Table 3-22: Lab Function Distribution, Cross-Referenced by Brand
Table 3-23: Applications Run on System, by Brand of Reader
Figure 3-11: Applications Run on System, by Brand of Reader
Table 3-24: Applications Most Likely to Increase
Figure 3-12: Applications Most Likely to Increase
Table 3-25: Number of Samples/ Month, by Brand (# of Scanners)
Table 3-26: Number of Samples/ Month, by Brand (% of Scanners)
Table 3-27: # Samples/ Month by Brand, Cross-Referenced by # Samples
Table 3-26: Microarray Brand(s) Used Most by Reader (# of Readers)
Table 3-27: Microarray Brand(s) Used Most by Reader (% of Readers)
Table 3-28: Brands Used by Reader, Cross-Referenced by Chip Brand
Table 3-29: Top Three Microarrays Used, by Brand
Table 3-30: Percentage Usage of Catalog vs Custom Chips
Figure 3-13: Percentage Usage of Catalog vs Custom Chips
Table 3-31: Source(s) of Custom Microarrays/ Probes (% of Labs)
Figure 3-14: Source(s) of Custom Microarrays/ Probes (% of Labs)
Table 3-32: Outsourcing of Microarray Samples
Figure 3-15: Outsourcing of Microarray Samples
Table 3-33: Reasons for Outsourcing Microarray Samples
Figure 3-16: Reasons for Outsourcing Microarray Samples
Table 3-34: Systems Used to Check Concentration, Size, Quality
Figure 3-17: Systems Used to Check Concentration, Size, Quality
CHAPTER FOUR: PREFERENCES AND EVALUATIONS
Table 4-1: Microarray Systems Ratings, by Major Brands (Cost, Throughput, Software, Dynamic Range, Ease of Use, Content on Arrays, Sample Size, Customer Service)
Figure 4-1: Microarray Systems Ratings, by Brand (Cost, Throughput, Software, Dynamic Range, Ease of Use, Content on Arrays, Sample Size, Customer Service)
Table 4-2: Features/ Steps to Improve or Change, by Brand
Table 4-3: Features/ Steps to Improve or Change, by Brand
Table 4-4: Bottleneck Where Samples Back Up, by Brand(Sample Prep, Fluidics, Labeling, Scanning, Data Analysis, Personnel, Hybridization, Other )
Table 4-5: Bottleneck Where Samples Back Up, by Brand (Sample Prep, Fluidics, Labeling, Scanning, Data Analysis, Personnel, Hybridization, Other )
Table 4-6: Criteria for Choosing Sample Preparation Products (Precedence, Cost, Ease of Use, Reproducibility, Throughput, Automation, Small Sample, Customer Service, Other)
Figure 4-2: Criteria for Choosing Sample Preparation Products (Precedence, Cost, Ease of Use, Reproducibility, Throughput, Automation, Small Sample, Customer Service, Other)
Table 4-7: Brands Used Most for RNA/ DNA Extraction
Figure 4-3: Brands Used Most for RNA/ DNA Extraction
Table 4-8: Brands Used Most for Amplification and Labeling
Figure 4-4: Brands Used Most for Amplification and Labeling
Table 4-9: Difficulty of Data Analysis
Figure 4-5: Difficulty of Data Analysis
Table 4-10: Difficult of Data Management
Figure 4-6: Difficulty of Data Management
CHAPTER FIVE: FUTURE PURCHASE PLANS
Table 5-1: Planned Purchases of Systems Within Two Years
Figure 5-1: Planned Purchases of Systems Within Two Years
Table 5-2: Time-Frame of Purchase Plans Within Two Years
Figure 5-2: Time-Frame of Purchase Plans Within Two Years
Table 5-3: Brands of Planned System Purchases
Figure 5-3: Brands of Planned System Purchases
Table 5-4: System(s) Labs Would Choose Today for Same Applications
Figure 5-4: System(s) Labs Would Choose Today for Same Applications
Table 5-5: Impact of Next-Gen Sequencing