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Reports

2008 Gene Expression Profiling Dashboard Series 2 -

pic_gene_expressionCatalog number: 0804GEP
Publication date: April 2008
Company-wide electronic copy: Complimentary

Please enquire about single-user* electronic copy pricing
* single-user pricing is intended for small companies, of 40 or less employees, to access The Life Science Dashboard. Please order these copies directly with Percepta Associates.

Overview

Overview

Gene expression profiling methods enable the quantification of multiple transcripts in a single RNA sample. Powerful and continually evolving methods, such as microarray analysis, multiplex PCR and quantitative real-time RT-PCR, are integral to deciphering the molecular mechanisms involved in development and disease, and are important tools in the identification of new drug targets.

Percepta’s 2008 Gene Expression Profiling Dashboard™ dives deeply into the characteristics and dynamics of the market for gene expression profiling products. This 2008 Dashboard provides a snapshot of the current market landscape that can be compared with data from the 2007 Gene Expression Profiling Dashboard, providing an ongoing story of how the market is adapting to new products, new competitors and new sales and marketing strategies.

The 2008 Gene Expression Profiling Dashboard™ was developed from responses to a 21-question survey completed by 312 scientists predominantly located in North America and Europe. 255 of these respondents perform gene expression profiling methods on a regular basis. This Dashboard reveals key market indicators for the gene expression profiling market as a whole as well as for the following methods representing market sub-segments:

  • Microarray-based gene expression studies
  • Serial Analysis of Gene Expression (SAGE) studies
  • Differential gene expression studies using multiplex PCR
  • qRT-PCR (cDNA template) using gene specific fluorescent probe
  • qRT-PCR (cDNA template) using non-specific SYBR Green
  • Northern blot analysis
  • Transcriptome studies using tiling arrays
  • Transcriptome studies via short-read sequencing

Survey Methodology

In January of 2008, Percepta fielded the Gene Expression Profiling Survey to a subset of the company’s panel of life scientists. Individuals were invited by e-mail blast to click through to a webpage at bioanalytix.com where the survey was hosted. Invitations were delivered on January 22, 2008 and results collected through February 1. A total of 312 scientists completed the survey, of which 255 are actively engaged in performing gene expression profiling experiments. Results based on the aggregate of collected responses are revealed in this Gene Expression Profiling Dashboard.

Respondent Demographics

Respondents from the academic, government and commercial market segments are well represented, with approximately 17% of respondents employed in an industry setting. About 82% of respondents are from North America, while 15% reside in Europe.

Junior (Lab Tech, Grad Students), mid level (Post-Doc, Lab Manager) and senior (Professor/PI, Group Leader) scientists are well represented in the data set, with the most cited job titles being Scientist/Senior Scientist (20.8% of respondents), Professor/Principal Investigator (16.3%) and Post-Doctoral Fellow (15.7%).

A wide variety of scientific areas of specialization is also evident, led by molecular biology (named by 34.1% of respondents as their primary area of expertise), biochemistry (10.6%) and cell biology (8.2%). Genomics (6.4%), microbiology/infectious disease/virology (6.1%), neuroscience (5.8%) and immunology (5.1%) are the only other applications named by more than 5% of respondents.

Small (1 to 5 scientists), mid-size ( 6 to 10 scientists) and large laboratories (>10 scientists) are well represented in the respondent data set. A total of 40.8% of survey participants work in labs where one to five people perform experiments. 29.4% are employed in labs with six to ten scientists, while the remaining 29.7% of respondents work in labs where greater than 10 individuals work at the bench.

Table of contents

Table of Contents

  • 9 Executive Summary
  • 11 Key Findings and Implications
  • 15 Gene Expression Profiling Dashboard
  • 19 Gene Expression Profiling Market Opportunity Matrix
  • 21 Survey Methodology
  • 23 Survey Invitation Text
  • 24 Respondent Demographics
  • 37 Frequency of Performance of Life Science Techniques
  • 42 Frequency of Performance of Gene Expression Profiling Methods
  • 58 Reaction Throughput and Market Growth Rates
  • 65 Respondent’s Stated Price Per Reaction
  • 68 Total Market Size, Market Segment Sizes and Total Market Growth Rate
  • 70 Market Shares by Segment (Share of Mention)
  • 84 Customer Satisfaction And Interest In Switching Suppliers
  • 89 Product Features That Influence Purchasing Decisions
  • 93 Primary Downstream Applications
  • 113 Desired Changes to Gene Expression Profiling Products
  • 120 Survey Questionnaire

Figures and Tables

  • 26 Figure 1: Respondent’s Place of Employment
  • 28 Figure 2: Respondent’s Country/Region
  • 30 Figure 3: Respondent’s Job Title
  • 32 Figure 4A: Respondent’s Areas of Expertise/Specialization
  • 33 Figure 4B: Respondent’s Areas of Expertise/Specialization (Molecular Biology Excluded)
  • 36 Figure 5: Number of Employees in Respondent’s Laboratories
  • 39 Figure 6: Percentage of Respondents Performing Various Techniques at Least a Few Times per Year
  • 44 Figure 7: Percentage of Respondents Performing Gene Expression Profiling Experiments
  • 45 Figure 8: Percentage of Respondents Performing Various Gene Expression Profiling Techniques at Least a Few Times per Year
  • 47 Figure 9: Percentage of Respondents That Perform Microarray-Based Gene Expression Studies
  • 48 Figure 10: Percentage of Respondents That Perform Serial Analysis of Gene Expression (SAGE) Studies
  • 49 Figure 11: Percentage of Respondents That Perform Differential Gene Expression Studies Using Multiplex PCR
  • 50 Figure 12: Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
  • 51 Figure 13: Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
  • 52 Figure 14: Percentage of Respondents That Perform Northern Blot Analysis
  • 53 Figure 15: Percentage of Respondents That Perform Transcriptome Studies Using Tiling Arrays
  • 54 Figure 16: Percentage of Respondents That Perform Transcriptome Studies via Short Read Sequencing
  • 73 Figure 17: Respondent’s Primary Supplier for Microarray-Based Gene Expression Studies
  • 75 Figure 18: Respondent’s Primary Supplier for Differential Gene Expression Studies Using Multiplex PCR
  • 77 Figure 19: Respondent’s Primary Supplier for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
  • 79 Figure 20: Respondent’s Primary Supplier for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
  • 81 Figure 21: Respondent’s Primary Supplier for Northern Blot Analysis
  • 88 Figure 22: Percentage of Respondents That Have Switched Suppliers in the Last Six Months
  • 91 Figure 23: Most Important Features of Products for Gene Expression Profiling Experiments
  • 96 Figure 24: Respondent’s Primary Downstream Application for Microarray-Based Gene Expression Studies
  • 98 Figure 25: Respondent’s Primary Downstream Application for Serial Analysis of Gene Expression (SAGE) Studies
  • 100 Figure 26: Respondent’s Primary Downstream Application for Differential Gene Expression Studies Using Multiplex PCR
  • 102 Figure 27: Respondent’s Primary Downstream Application for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
  • 104 Figure 28: Respondent’s Primary Downstream Application for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
  • 106 Figure 29: Respondent’s Primary Downstream Application for Northern Blot Analysis
  • 108 Figure 30: Respondent’s Primary Downstream Application for Transcriptome Studies Using Tiling Arrays
  • 110 Figure 31: Respondent’s Primary Downstream Application for Transcriptome Studies via Short Read Sequencing
  • 34 Table 1: Respondent’s Areas of Expertise/Specialization Values for Figures 4A and 4B
  • 40 Table 2: Frequency of Performance of Various Techniques
  • 41 Table 3: Frequency of Co-Performance of Various Molecular Biology Techniques
  • 46 Table 4: Frequency of Performance of Gene Expression Profiling Methods
  • 56 Table 5: Frequency of Co-Performance of Life Science Techniques with Gene Expression Profiling Methods
  • 57 Table 6: Frequency of Co-Performance of Gene Expression Profiling Methods with Life Science Techniques
  • 60 Table 7: Median and Average Monthly Throughput for Gene Expression Profiling Products
  • 61 Table 8: Percentage of Respondents Performing Various Numbers of Gene Expression Profiling Reactions Per Month
  • 62 Table 9: Highest Throughput Users: Comparison to 2007 Life Science Dashboard
  • 64 Table 10: Projected Growth in the Performance of Various Gene Expression Profiling Techniques
  • 67 Table 11: Median and Average Price Per Prep for Gene Expression Profiling Products
  • 83 Table 12: Market Share Leaders for Gene Expression Profiling Products
  • 86 Table 13: Percentage of Respondents Satisfied with Various Gene Expression Profiling Products and Reasons for Dissatisfaction
  • 87 Table 14: Respondent’s Interest in Switching to a New Supplier for Gene Expression Profiling Systems: Comparison to 2007 Life Science Dashboard
  • 92 Table 15: Most Important Features of Products for Gene Expression Profiling Experiments – Comparison to 2007 Gene Expression Profiling Dashboard
  • 112 Table 16: Respondents Primary Application After Various Gene Expression Profiling Methods

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