A National Cancer Institute Comprehensive Cancer Center


Shared Resources



Experimental Design

When you first begin to consider using microarray technology to answer questions related to your research, the very first step you should take is a discussion of experimental design with Dr. Craig Tomlinson, director of the DGML. He will meet with you to talk about your questions and to help construct an effective design that will help you answer those questions using the microarray facilities. There are many factors that must be considered when using microarrays, including:

  • What questions are you trying to answer?
  • What type of tissue/cells do you plan to use?
  • How easy or difficult it is to obtain quality RNA from your samples?
  • What RNA isolation technique is appropriate for your chosen tissues or cells?
  • How much RNA can you actually obtain from your sample?
  • How many replicates are needed to obtain statistical sigficance?
  • How do you intend to analyze and interpret your array results

There are dozens of experimental variables that may affect microarray experiments, and every researcher's goal should be to eliminate as many of those sources of variation as possible through good experimental design. Some variables to be aware of are:

  • Procedural variation - sample collection and RNA isolation
  • Technician variation - Arrays are notoriously finicky. Ensuring that the same technician handles all samples in an experiment is necessary.
  • Equipment variation
  • Reagent variation - different lot numbers and different preparers
  • Starting material - RNA concentration and quality needs to be checked every time; make sure the amount of starting material is the same for every chip in the experiment.

The DGML can reduce many of those variables by providing full service to researchers. We will begin with quality RNA or DNA (provided by the user) and perform all of the sample preparation and chip processing on our equipment. Therefore, the researcher can be assurred that the majority of detected variation is biological.

A good starting reference for any researcher thinking about using microarray technology is a recent paper in Nature Reviews Genetics: Expression Profiling - Best Practices for Data Generation and Interpretation in Clinical Trials. It gives a good introduction into the best practices for performing a microarray study.

To learn more about how to design your next microarray experiment, please contact the Microarray Core director, Craig Tomlinson, to set up an appointment.