Analysing biological data by model fitting in GraphPad Prism
Monday, 11 November 2019, 9.30am to 12pmApply for this course
This half-day classroom based MSD Skills Training course is suitable for all postgraduate research students and postdoctoral early career researchers looking to fit, compare and analyse biological data using model fitting in Prism.
Experimental biologists often need to compare the outcome of multiple treatments when data is collected over multiple doses or time points. Consider the experimental data shown in Fig 1 (see PDF). How do we determine if the two dose-response curves in Fig. 1A or the two time-course curves in Fig. 1B are statistically different? A common approach is to repeat the measurement multiple times at a single dose or time point and perform a relevant statistical test (e.g. a t-test). A drawback of this procedure is that it masks effects that may only be apparent at different doses or time points. These effects, that are dose or time-dependent, often provide useful mechanistic insights. In this tutorial, we explain how to statistically compare multiple treatment curves directly, without the need for repeated measurements, and highlight the utility of the procedure in revealing mechanistic insights. No prior knowledge of mathematical modelling or statistics will be assumed and discussion will be restricted to tools available in Graphpad Prism. Participants are encouraged to bring their own data, which they can analyse with assistance in the last section of the course.
The course contains four sections:
1. Examples of biological data where model fitting is useful.
2. How to fit biological data to models (including how to assess the quality of a fit, the effects of noise, and the effects of incomplete data).
3. How to compare two data sets using model fitting.
4. Case studies and analysis of your own data.
Sections 1-3 (above) will begin with a lecture followed by a live demonstration in Prism. Participants will then use Prism to carry out exercises themselves. In the last section, participants will analyse three case studies and/or their own data. Instructors will be available throughout the workshop for assistance.
The total course length is 2 hours (3 sections that include a 15 minute lecture & 15 minute practical plus 30 minutes of case study analysis). The tutor also offers a tutorial style period at the end of the session for students to obtain personal help.