Pricing

Where do I start?

If you are a new user, it is highly recommended that you consult with the Core Director prior to starting an experiment. The experimental design is critical for generating interpretable data. In general, the biological variability is greater than the technical variability, so replicates should be independent biological experiments. The following is a list of important considerations:

  • What is the biological question/hypothesis?
  • What is the origin of the samples?
  • How will the RNA be extracted
  • What chips should I use?
  • How many replicates should I use per condition?
  • Should I pool samples?
  • Can I standardize the experimental manipulations and extraction procedures to minimize variation?
  • What comparisons do I wish to make?
  • How will I analyze the data?

A number of publications have addressed the design of microarray experiments:

Bolstad et al. Experimental design and low-level analysis of microarray data. Int Rev Neurobiol. 2004;60:25-58.

Leung & Cavalieri. Fundamentals of cDNA microarray data analysis. Trends Genet. 2003:19:649-59

Churchill. Fundamentals of experimental design for cDNA microarrays. Nat Genet. 2002 Dec;32 Suppl:490-5.

Sample pooling for microarray analysis: a statistical; assessment of risks and benefits. Affymetrix tech note 2004

Wei et al. Sample size for detecting differentially expressed genes in microarray experiments. BMC Genomics 2004, 5:87

 

 

 

 

 

 

 

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