Chapter 9 Analyze the Comparative C
T
Experiment
Design a Study
191
Applied Biosystems 7500/7500 Fast Real-Time PCR System Getting Started Guide for Relative Standard Curve
and Comparative C
T
Experiments
Notes
Design
Guidelines
When you design your own comparative C
T
study:
• Enter an study name that is descriptive and easy to remember. You can enter up to
100 characters in the Study Name field. You cannot use the following
characters in
the Study Name field: / \ > < * ? " | : ;
Note: The study name is used as the default file name.
• (Optional) Enter a user name to identify the owner of the study. You can enter up to
100 characters in the User Name field.
• (Optional) Enter comments to describe the study. You can enter up to
1000 characters in the Comments field.
• Add up to 100 comparative C
T
experiments to the study.
To add experiments to a study they must have:
– One or more common endogenous control(s).
– Identical thermal cycling parameters (the same number of steps, cycles, sample
volume, and emulation mode).
IMPORTANT! The 7500 software cannot combine in the same study experiments
that use Fast and standard thermal cycling conditions.
IMPORTANT!
The 7500 software automatically analyzes a study after more than one
experiment is added to it. Consequently, to ensure that the software uses the correct
settings, Applied Biosystems recommends that you review the analysis settings of
your study after adding multiple experiments.
Note: The 7500 software automatically assigns the endogenous control and
reference sample for a study based on the analysis settings of the first experiment
added to it.
Note: If experiments that contain biological replicate groups are added to a study,
the 7500 software automatically merges the matching biological groups.
• When adding experiments to the study, Ctrl+click multiple experiments in the Open
dialog box to add them to the study.
• Select an experiment that has been added to the study to view its properties in the
Properties pane.
• Filter the experiments added to the study to simplify the list for easier review. See
“How to Simplify Data Lists Using the Filter Query” on page 192.
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