Hilbert curves can be used to effectively visualize genomic data, because they can provide a global overview of genome-scale datasets while still revealing the spatial distribution of features at high resolution. Hilbert curve visualization has been utilized to compare the sequence difference between human and other primates, to show the spatial organization of different chromatin states, and to investigate the genome-wide distribution of histone modifications.
This tool allows to display very long data vectors in a space-efficient manner, allowing the user to visually judge the large scale structure and distribution of features simultaneously with the rough shape and intensity of individual features.
Visualizes long vectors of integer data by means of Hilbert curves. HilbertVisGUI allows to display very long data vectors in a space-efficient manner, allowing the user to visually judge the large-scale structure and distribution of features simultaneously with the rough shape and intensity of individual features. A typical use case is ChIP-Chip and ChIP-Seq, or basically all the kinds of genomic data, that are conventionally displayed as quantitative track ("wiggle data") in genome browsers such as those provided by Ensemble or UCSC.
A tool to visualize read-depth and pair-end information as it originally comes from NGS machines at various resolutions. Its main purpose is to provide intuitive visualizations for an easier exploration or detections of structural variations. With Meander, users can explore variations at different levels of resolution and simultaneously compare up to four different individuals against a common reference.
Hilbert curves enable high-resolution visualization of genomic data on a chromosome- or genome-wide scale. The HilbertCurve package provides an easy-to-use interface for mapping genomic data to Hilbert curves. The package transforms the curve as a virtual axis, thereby hiding the details of the curve construction from the user. HilbertCurve supports multiple-layer overlay that makes it a powerful tool to correlate the spatial distribution of multiple feature types. HilbertCurve greatly facilitates the visualization and interpretation of the ever increasing number of genome-wide datasets generated by next-generation sequencing and other omics techniques.