# SVEDBERG - hands-on software workshop

## Getting Confidence Limits for the Properties of Each Peak in your c(s) Distribution Using the Program SVEDBERG

**Prerequisites:**

at least some familiarity with c(s) analysis in SEDFIT (or similar size-distribution methods in ULTRASCAN)

#### Presenter: John Philo, Alliance Protein Laboratories

**Description**

Although sedimentation coefficient distributions are widely used to identify what species (peaks) are present in a sample, it is usually not straightforward to determine the confidence limits for the properties of those species. In particular, SEDFIT provides no information about the precision of the peak fractions, which in many cases is the property of most interest. Furthermore, although SEDFIT can use Monte-Carlo approaches to try to assess a confidence region for each point (sedimentation coefficient) in the c(s) curve, that approach can be misleading because it doesn't explicitly deal with the fact that there is uncertainty in the position of each peak. A third important point is that Monte-Carlo approaches assume the noise in the raw data is randomly distributed, which is not ever really true for AUC data.

This workshop will show you how to use the user-friendly, public-domain program SVEDBERG to easily translate your c(s) distribution to a mixture model and obtain confidence limits for the peak fractions, sedimentation coefficient, and the molar mass for each peak using any of three different statistical approaches (including the bootstrap method, which makes no assumptions about the noise in the data being random).

The workshop will also describe how we can use SVEDBERG to sequentially release the built-in constraint of the c(s) method that every species has the same hydrodynamic shape (f/f0 ratio), and thereby learn how much information about the molar mass (or shape) of each species is really present in the raw data.

This workshop is presented on Monday during session 9, and repeated during session 10.