DCDT+ Home Page

DCDT+

What is DCDT+?

DCDT+ is a Windows^®program for analysis of sedimentation velocity (SV) data that implements the dc/dt method originally developed by Walter Stafford, and also implements fitting of the derived g(s*) distributions as a mixture containing of up to 5 discrete (non-interacting) species. It has been used to analyze data for nearly 300 publications.

The program is designed to be very easy to use, even for novices, yet it also offers many options for the 'power user' when they are needed. It uses multi-page analysis 'documents' and a familiar user interface with toolbars and buttons, making it similar to other Windows programs to reduce the learning curve. It also incorporates a number of intelligent 'wizards' that automatically accomplish tasks such as locating the meniscus position, removal of systematic noise ("jitter") and fringe jumps from interference scans, and even selection of which scans should be used for analysis.

This is not a package that tries to do everything---its purpose is to implement one particular approach, do that very well and very easily, and do it in a highly reproducible and well-documented manner.

The success of this approach is demonstrated by its use in 200+ publications. More significantly, many of these are from intermittent or casual users of AUC, proving you don't have to devote years to learning data analysis to successfully answer important research questions with SV.

The program is now distributed as "freeware" and requires no registration. The only restriction is that it cannot be sold or packaged with other commercial software. The author asks only that you cite it properly when publishing your analyzed results.

Unique features:

Modern multi-document, Explorer-style user interface

multiple analyses can be open simultaneously, and their g(s*) distributions are automatically incorporated into an overlay graph [example below]

Explorer-like navigation tree to move to specific analysis pages (analysis steps) and between analysis documents

click-and-drag setting of meniscus marker, data limits, peak limits etc. [see image below]

	New algorithm for fitting of g(s)* distributions or dc/dt curves as mixtures gives s, D, and M values for each species with theoretical accuracy of better than 0.1%, independent of the number of scans used in the analysis
	Load the entire run and then use scroll bars to select the subset of scans to be analyzed (or just let the program wizard do it for you) [see image below]

Optionally normalizes g(s*) distributions to allow easy comparisons of samples at different concentrations (a great diagnostic to distinguish interacting systems from mixtures, as in example shown 3 pictures above)

'Standard' program mode alters user interface to hide options you probably don't need; 'Advanced' mode provides more options to power users

Program wizards automatically accomplish many tasks

Once scans are loaded, you can can calculate the g(s*) distribution and go all the way to a completed fit as a single species simply by repeatedly hitting the Enter key to accept the wizards' default choices

New! Generates a log file that records every step of the data analysis, every option selected, every intermediate fitting result (including a table and graph), when it was done, and by whom (for computers with authenticated log-in servers)

Evaluates fitted parameter confidence intervals using any of three orthogonal approaches: F statistics, the bootstrap method, or a Monte Carlo algorithm that puts the random noise in the theoretical scans [to eliminate any concerns about effects of the transformation to g(s*)]

True local Help file to give context-sensitive Help for each dialog box or control, with extensive tutorials and a searchable index. (A PDF file to print a user manual is also available to registered users)

Generates nicely formatted printed reports with tables, and which document every factor that influences the results. These reports (with graphs) can be pasted into your word processor or electronic lab notebook

Saved analysis documents record every parameter, including the raw data, in a single file so you can re-load your analysis back to exactly the same state

Analysis documents appear in your 'My Recent Documents' folder, just like your other documents

Creates 9 types of publication-quality graphs of fit results

DCDT+ is used by more than 100 laboratories around the world (partial list here).

Jump to: Download it Now! | System Requirements | Revision history | User List | Publications

How does DCDT+ differ from the ORIGIN^® version of DCDT supplied by Beckman Coulter?

DCDT+ provides correct values of D and M from fitting the g(s*) distributions

the Beckman implementations (even the newest Origin 6 versions) contain an error in converting the width of the fitted Gaussians to diffusion coefficients; the returned D and M values are never accurate

Just load the entire run in one operation and then select which scans to analyze using slider controls

no more struggling to figure out which scans to load and analyze

DCDT+ provides a quick test for whether you are broadening the curves by including too many scans

get the best signal/noise possible without hoping and guessing about when you are averaging too many scans or struggling with cumbersome manual calculations

standard errors or confidence intervals are calculated for all fitted parameters

what good are fitting results if you don't know the uncertainty in the values returned?

DCDT+ comes with a comprehensive, local context-sensitive Help file and optional printed manual

includes step-by-step tutorials, tips, "how-to" guides, frequently-asked questions, a searchable index, and images of all forms

full reports of analyses are provided for documented, reproducible results

sedimentation coefficients can be internally converted to s_20,wvalues

DCDT+ provides a unique option of fitting to dc/dt curves, giving improved accuracy and improved resolution of multiple species in some cases

DCDT+ shows you the dc/dt curves for every individual scan pair so you can identify abnormal interference scans (outliers) before you unknowingly include them in your analyses

bad scans can be removed from the analysis without starting over and reloading all the scans

reproducible setting of the meniscus position

no more struggling with the Origin^® data marker and a tiny graph

results from fits give true molecular masses for any value of v-bar and density

no more cumbersome manual calculations

when the zero of the dc/dt curves is manually adjusted, that fact and the amount of the adjustment is documented in fit reports

what good are results that can't be documented or reproduced?

during multi-species fits the masses and/or sedimentation coefficients can be constrained to ratios appropriate for small oligomers

includes a Claverie finite-element velocity experiment simulator for "what-if" testing and self-teaching

unique option of using an alternative algorithm for calculating g(s*) distributions that works better than the standard Stafford algorithm when the time span of the scans grows long

computes the number-, weight-, z-, and z+1-average sedimentation coefficients and total concentration from both the g(s*) and g^(s*) distributions, with error bars for all these values

handles an unlimited number scans (up to available memory), not just 40

computes and displays g^(s*) (g-hat), the distribution that should be used when studying interacting systems, as well as g(s*)

How does DCDT+ differ from the ls-g(s) or c(s) methods in Peter Schuck's SEDFIT?

	The ls-g(s) distributions derived by SEDFIT are equivalent to the g(s)* distributions derived via the DCDT method only when the time span of the scans used in either method is small (a small number of scans). As the time span grows larger they become non-equivalent, and for ls-g(s) there is no longer any direct theoretical relationship between the width of a peak and the diffusion coefficient (or mass) of that species as there is for g(s)*.
	For g(s)* derived via the DCDT method the removal of baseline noise (time-independent noise) and interference 'jitter' (radially-independent noise) is done via simple arithmetic and is model-independent. For ls-g(s) and c(s) the removal of this systematic noise is model-dependent.
	For c(s) distributions the diffusion information is essentially removed, which enhances the resolution for mixtures. The peak widths in c(s) are a function of signal/noise ratio and regularization parameters; they have no physical meaning.
	False peaks are often generated if the ls-g(s) method is applied to scans encompassing a large fraction of the run, especially for samples where diffusion is significant (conditions where it does not provide a good fit of the raw data). The c(s) method also generates false peaks if not used very carefully or whenever it cannot generate a good fit of the raw data. *The dc/dt* method never generates false peaks.**
	Fitting of ls-g(s) distributions to one or more peaks is not implemented in SEDFIT; peak fitting makes no sense for c(s) distributions
	Neither ls-g(s) nor c(s) provides error bars for the distributions or properties of individual peaks
	SEDFIT does not provide reports, and does not store the analysis in a file so it can be re-opened
	SEDFIT cannot have multiple analyses open at the same time, and cannot overlay ls-g(s) or c(s) distributions from different samples
	SEDFIT does not have a local context-sensitive Help file with searchable index, or offer a printed manual

System Requirements

SVEDBERG 7 runs under Windows XP, Vista, 7, 8, or 10. Use via Windows dual-boot configurations on MacIntosh systems usually works fine, but is not officially supported or guaranteed.

This program also requires the Microsoft .NET framework to be present on the computer. This is usually already true for newer computers. If it is not already present, this is detected during installation and a link is given so it can be downloaded from Microsoft and installed.

Although DCDT+ will run correctly at a 640x480 (VGA) video resolution, a resolution of 1024 x 768 or higher is highly recommended.

The program requires approximately 8 MBytes of disk space (most of which is for the comprehensive Help file).

How should I cite this program?

The primary citation for this program is

Philo, J. S. (2006). Improved methods for fitting sedimentation coefficient distributions derived by time-derivative techniques. Anal. Biochem. 354, 238-246.

Because the original development of the dc/dt method was by Walter Stafford, please always also cite Walter Stafford's original paper:

Stafford, W.F., III. 1992. Boundary analysis in sedimentation transport experiments: A procedure for obtaining sedimentation coefficient distributions using the time derivative of the concentration profile. Analytical Biochemistry 203:295-301.

The program itself should be mentioned in your Methods section as DCDT+ by John Philo, with the version number.

Specialized method citations

The reference for the special multi-segment dc/dt calculations is

Philo, J. S. (2011). Limiting the sedimentation coefficient range for sedimentation velocity data analysis: Partial boundary modeling and g(s*) approaches revisited. Anal. Biochem. 412, 189-202.

The reference for fitting to dc/dt data rather than g(s*), and for the Use true mean time button (the 'broad algorithm') is:

Philo, J.S. (2000) A method for directly fitting the time derivative of sedimentation velocity data and an alternative algorithm for calculating sedimentation coefficient distribution functions. Analytical Biochemistry, 279, 151-163.