Briefly, F-Seq [129] is a parametric density estimator of sequence tag data, developed to overcome the bin-boundary effects of histogram metrics for peak enrichment [129]. F-seq implements a smooth Gaussian kernel density estimation that takes into account the estimated center of each sequence read. F-seq has been implemented in a number of studies [17, 19, 79, 94] for the identification of chromatin accessibility and the evaluation of TF footprints in relation to ChIP-seq data [17, 19, 79, 94]. However, it requires time-consuming designing for statistical testing [137]. The Hotspot algorithm [21, 130] has been widely used by the ENCODE consortium to identify regions of chromatin accessibility and represents, to our knowledge, the only DNase-seq-specific algorithm that reports statistical significance for identified DHSs [128]. The algorithm isolates localized DHS peaks within areas of increased nuclease sensitivity (‘hotspots’). Results are evaluated with false discovery rate analysis for statistical significance, employing generation of a random dataset with the same number of reads as the analyzed dataset. The newest version of Hotspot, DNase2hotspots, merges the two-pass detection in the original algorithm into a single-pass [130].
