Fig. 9: Clustering-based analysis of replication progression on SMLM data.

Super-resolution images were reconstructed in the SMAP software (A). Image thresholding using cluster density calculator (B) to eliminate localizations from low-density regions. C Detection of clusters using the DBSCAN algorithm. Quantifying the number of clusters in wt, fas1 and nuc1 mutants using the Kruskal–Wallis H-test, n = number of cells analysed (H-statistic = 5.092; p = 0.078; degrees of freedom = 2). D Differences between groups have been estimated with the Wilcoxon rank-sum test (two-sided). Experiments were performed in three biological replicates. Means are indicated by white circles, medians are indicated by the line inside the box, minimum and maximum values are defined by the whiskers, percentiles (25% and 75%) are indicated by the top and bottom edges of the box. Confidence intervals (95%) for the median in the wild-type, fas1 and nuc1 cluster analysis are [69:245] for wild-type data, [54.5:146] for fas1 and [46:90] for nuc1. Source data are provided as a source data file (sheet 3—DBSCAN clustering analysis). k: minimum objects in the neighbourhood, eps: neighbourhood radius. Scale bar: 1 µm.