title: A histogram approach to the quality of fit in sedimentation velocity analyses.
abstract: The quality of fit of sedimentation velocity data is critical to judge the veracity of the sedimentation model and accuracy of the derived macromolecular parameters. Absolute statistical measures are usually complicated by the presence of characteristic systematic errors and run-to-run variation in the stochastic noise of data acquisition. We present a new graphical approach to visualize systematic deviations between data and model in the form of a histogram of residuals. In comparison with the ideally expected Gaussian distribution, it can provide a robust measure of fit quality and be used to flag poor models.
authors.affiliation: Dynamics of Macromolecular Assembly Section, Laboratory of Cellular Imaging and Macromolecular Biophysics, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD 20892, USA.
authors.forename: Jia
authors.initials: J
authors.lastname: Ma
authors.affiliation: Dynamics of Macromolecular Assembly Section, Laboratory of Cellular Imaging and Macromolecular Biophysics, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD 20892, USA.
authors.forename: Huaying
authors.initials: H
authors.lastname: Zhao
authors.affiliation: Dynamics of Macromolecular Assembly Section, Laboratory of Cellular Imaging and Macromolecular Biophysics, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: schuckp@mail.nih.gov.
authors.forename: Peter
authors.initials: P
authors.lastname: Schuck
mesh_terms: D006801:Humans; D008962:Models, Theoretical; D013223:Statistics as Topic; D014461:Ultracentrifugation / Q000379:methods* / Q000592:standards*
keywords: Analytical ultracentrifugation; Sedimentation velocity