Fig. 1: Sperm motility landscape resulting from a (Barnes-Hut approximation) t-SNE dimensional reduction.

a Kernel density showing the high- and low-density regions within the landscape, computed in a 200 × 200 cell grid with a neighbouring parameter representing a 1% of the dataset size (perplexity = 639). b Clustering using a watershed algorithm allowing the discretization of data into clusters (delimited by the white lines), and depicting the highest density peak within each cluster (black triangles). The legend describes the colour gradient in the density kernel. This analysis involves functions "bdm.pakde" and "bdm.wtt" in the bigMap R package. See also "Sperm motility landscape" in Methods and Garriga & Bartumeus 2018⁷⁵).