TITLE: Fitting of SAXS data using SCATTER 
AUTHORS: Chris Berndsen

[DESCRIPTION]
<div class = "text-blocks"><div class = "text-block">Scatter is a Java-based Small Angle X-ray Scattering software developed by Rob Rambo. It can be used for processing and analyzing data to calculate Rg, Dmax, and other parameters. If the ATSAS package is installed, Scatter can also access DAMMIN/DAMMIF to produce dummy atom models fitted to the data. </div><div class = "text-block">This protocol was written for students at James Madison University to fit SAXS data in instructional or research lab settings. </div></div>

[STEPS]
?. [Buffer subtraction]
Start  and select Subtract from the left side menu.
?. [Buffer subtraction]
Drag your .dat files collected on your sample into the top pane.
?. [Buffer subtraction]
Drag your .dat files collected on your buffer into the bottom pane.
?. [Buffer subtraction]
Look at the similarity vs. frame window and determine if there are signs of radiation damage. This would shown by a deviation from the average in either the sample or buffer window.
?. [Buffer subtraction]
Set the range in the box for which frames to start and end with in the final file.
?. [Buffer subtraction]
Set the options for the output directory and files
?. [Buffer subtraction]
Set the output directory as a sub-folder of the data directory named:[Well_number]_[proteinname]_analysisRecord the output directory as a note on this step.
?. [Buffer subtraction]
Set the output file name:[Well_number]_[proteinname]_[#_dat_files]_subtracted
?. [Buffer subtraction]
Click the subtract button and wait.
?. [Buffer subtraction]
Look at the PDF report before doing further analysis.
?. [Buffer subtraction]
If the report suggests too many dat files were included, reduce the number of dat files incorporated in step 4.1 and repeat the subtraction steps making sure to change the file name.
?. [Analysis of data]
Switch to the analysis pane on the left side.
?. [Analysis of data]
If coming straight from subtraction, the average and median data sets will already be loaded. If not, drag the average or median dataset into the lower panel to the data set window.
You can load multiple data sets to analyze and compare. To analyze a data set, check the box next to the data set name and uncheck all the others.
?. [Analysis of data]
Press the G button at the right side of the data set window to begin Guinier analysis which will give an estimate of the radius of gyration.
The radius of gyration is average electron density weighted squared distance of the scatters from the center of the object. This can be thought of the radius of the molecule if the molecule was a perfect sphere.
?. [Analysis of data]
In the analysis pane are three main areas:
?. [Analysis of data]
Press the Rx analysis button in the analysis menu to estimate the radius of the cross section.
This radius will be identical to the Rg for a perfect sphere. Other shapes will have a value less than Rg and this can be useful for suggesting deviations from globular. For example for B-form DNA, the cross-section radius is ~10 A.
?. [Analysis of data]
The G button brings up two panels, one a re-plot of the data to linearize the beginning portions of the data and a residuals plot of the fit line in the top panel to the data. Adjust the number of points using the arrows at the bottom right until the top panel red ine fits the data and the residuals. Residuals should be randomly scattered around the horizontal line.Important: the q x Rg limits should be between 0 and 1.3.
?. [Analysis of data]
Close the window and the new Rg will appear in the data set window under Rg.
?. [Analysis of data]
Click to the Guinier peak analysis to bring up a window to check your fitting. Ideally the data peaks at the crossing of the dashed lines and the dashed red line goes through the data points.The Gunier peak window will also appear and you can adjust the fit if needed. If you do adjust the fit, record the new start and end number in a new row in step 9.2 above and note that you changed the range later
?. [Analysis of data]
The window that appears will have a re-plot of the data and a residual plot of the data below. Fit the data so that the q x Rg is between 0 and 1.3 and the residuals are randomly scattered around the red line.
The cross section radius is determined by fitting the data at q values immediately adjacent to the Guinier region but slight larger.
?. [Analysis of data]
Press the Volume button in the analysis menu to estimate the volume of the sample
?. [Sample Information]
Record your sample information in the table below.  Add rows as needed.  AB1Sample parameters2Protein/molecule name3Concentration (mg/ml)4Uniprot ID5Number of amino acids/residues6Crystal structures7Well number (if SiBYLS HT-SAXS)8Molecular weight (kDa)9Sequence
AB1Sample parameters2Protein/molecule name3Concentration (mg/ml)4Uniprot ID5Number of amino acids/residues6Crystal structures7Well number (if SiBYLS HT-SAXS)8Molecular weight (kDa)9Sequence
?. [Buffer subtraction]
Record the ranges for the sample and buffer in a note below.
?. [Analysis of data]
Record the start and end q2 values below  ABC1StartEnd2Rg (Guinier) data range
ABC1StartEnd2Rg (Guinier) data range
?. [Analysis of data]
Record the start and end q2 values below  ABC1StartEnd2Rc
ABC1StartEnd2Rc
?. [Analysis of data]
Adjust the start and end values until the blue line in the Porod-Debye plot fits in the latter portion of the plot with a positive slope (example shown below). The residuals plot should show random scatter around the line.
For multi-domain proteins, this analysis can be tricky to do.
?. [Analysis of data]
Record the values in the table.  AB1Volume (A^3)2Q3P4start5end
AB1Volume (A^3)2Q3P4start5end
Values of P less than 4 can suggest some disorder in the molecule. The Volume should approximate the volume of the crystal structure. Deviations can suggest aggregation, quaternary structure, or flexibility.  Analysis of the Kratky plot and/or the data plot can help distinguish between these possibilities
?. [Analysis of data]
Press the Vc plot button to display the re-plotted data.
The left side plot should be continous and not show any gaps. The right side plot should level out at high q values. Bad buffer subtraction can show up as discontinuities in the total scattered intensity plot or a non-level integrated area plot.
?. [P(r) plot]
Press the P(r) button on the right side to start real-space analysis.
?. [P(r) plot]
Right click on the data set and select the FIND DMAX option in the pop-up menu. This will bring up a window to automatically estimate DMAX, or the maximum distance between atoms in the molecule.
?. [P(r) plot]
In the resulting window, Scatter will predict an optimal data range to calculate Dmax. The default settings for Dmax are to search between 50 and 200 Ångstroms, however this can be adjusted for smaller proteins or to a narrower range, which will speed up calculations.
?. [P(r) plot]
Press the start button to calculate and wait for the progress bar to finish.
?. [P(r) plot]
The top left panel should show a normally distributed peak surrounding the most likely Dmax value. The number will be shown below the plots. The left side plot will show a rough P(r) plot.
?. [P(r) plot]
In the data set window of the P(r) area, input the Dmax from 14.4 into the Dmax option.
?. [P(r) plot]
Record the Dmax value here  AB1Dmax
AB1Dmax
?. [P(r) plot]
Generally data above q = 0.25 don't add much to the fitting, so it is fine to truncate the data used for fitting. Adjust the end value and record the start and end values below.  AB1StartEnd2
AB1StartEnd2
?. [P(r) plot]
The data below are a bad fit. The P(r) plot should slowly approach zero at high radius values and the fit line should fit well to hte raw data at right.
?. [P(r) plot]
Adjust Dmax up or down to improve the fit. The plot in 15.2 indicates a larger Dmax should be used. If the 0 line in the P(r) plot is significantly removed from the x-axis or the line in the left plot are below the x-axis, then a smaller Dmax should be used.
?. [P(r) plot]
Once a reasonable Dmax has been found, the data should appear as below.  Press refine to confirm the fit.
?. [P(r) plot]
Once refinement has finished, the cross validation plot will appear and outliers are shown in red. Any outliers should be randomly distributed across the data and to a minimum.
?. [P(r) plot]
Record the final Dmax and other parameters below.  AB1Dmax2Real Rg3Real I(0)4Score5r (ave)
AB1Dmax2Real Rg3Real I(0)4Score5r (ave)
?. [Exporting the data to file]
Return to the Analysis window in the left side menu
?. [P(r) plot]
Press the 2File button in the data analysis window to save the P(r) data. The filename should be as[Well_number]_[proteinname]_prScatter will save this as a .out file which will be used for model-free analysis.  Record where this file is saved in a note in this step.
?. [Exporting the data to file]
Click the PDF option
?. [Exporting the data to file]
Name the PDF file[Well_number]_[proteinname]_reportIndicate the location of this file as a note attached to this step.
?. [Exporting the data to file]
The report contains 4 plots:log(I) v qthe normalized Kratky plot, which can indicate disorder and quaternary structuretotal scattered intensity plotthe P(r) distributionOn the second page, are the final numbers (with errors bars).