The cross-sectional radius-of-gyration, R_{c} is a useful parameter for samples that are highly asymmetric or elongated (see Chapter 4, p155 of Glatter and Kratky 1982). A similar q x R_{c} < 1.3 limit applies to the upper q-region (Figure 1); however, the lower q-region tends to be much more worrisome as it is severely corrupted by the transformation (Figure 1). To start, click "Rx Analysis" button near the middle part of the panel (Figure 1). This will pop up the R_{c} plot which is divided into the upper fit and lower residuals plots.

- If plot does not appear, check "end" points in Analysis tab. Too few points and the plot will not appear.

The goal here is to find the first linear region on the righthand side of the hump in the upper plot. To start, trim back the high-q data from the end until q x R_{c} < 1.3. The hump originates from the first sinusoid of the Fourier transform. Sometimes, datasets may not contain this hump largely observed in samples with large R_{g} values implying more low q data would be required for a typical Guinier analysis. In these cases, an R_{g} will have to be determined using the P(r) distribution.

Here, the data was truncated to the first 188 points. This sets the putative limit q x R_{c} < 1.3. Now, we truncate the starting points to capture the first linear region. Please note, the R_{c} value is updated in the analysis tab (red arrow Figure 2).

After truncating the starting point to 95, more points were removed from the end (Figure 3 and 4) to maintain the q x R_{c} limit resulting in an R_{c} of 14.7. This would be a satisfactory fit. Having both R_{g} and R_{c} allows for the estimation of the maximum dimension (see Glatter and Kratky 1982, Chapter 8 page 258)