Fitting the statistical helix polymer model to random collision frequencies quantified at mouse gene-rich loci. 3C-qPCR data shown in Figure 2a and Additional file 1 (Usp22PE) were compiled into a single graph (upper panel). Error bars are standard error of the mean. The dashed lines delimit supranucleosomal domains as defined in Figure 2a. The graph shows the best fit analyses obtained with the linear polymer model (Equations 1 and 2a; black curve) or the statistical helix model (Equations 1 and 5; red curve). Correlation coefficients (R2) are indicated in the lower panel, which shows the same graph where collision frequencies are represented in a logarithmic scale. Best fit parameters for the statistical helix model are indicated within the graph (lower panel) and have been used to calculate the expected theoretical means of random collision frequencies for each supranucleosomal domain (numbers in brackets in upper panel), which are in good agreement with the means obtained from the experimental data (values indicated above the expected means). P-values (Mann-Whitney U-test) account for the significance of the differences observed between the experimental means of two adjacent domains. One can note, amongst the experimental points, a few outliers. To minimize the weight of these data points, we chose a non-parametric statistical test (double asterisks indicate a P-value < 0.05 and > 0.01 and triple asterisks a P-value < 0.01).
Court et al. Genome Biology 2011 12:R42 doi:10.1186/gb-2011-12-5-r42