Widgets
HiCognition implements the region-set focus approach (see the concept section for details) on a visualization level using widget collections and widgets. Widget collections represent a single set of genomic regions (e.g., Chip-Seq peaks of a target protein) and host one or more widgets representing genomic features (e.g., Chip-Seq tracks or Hi-C tracks).
Features are linked to genomic regions via preprocessing steps (see the preprocessing section for more details), which primarily represent data aggregation. Once preprocessing has linked features to genomic regions, they are available for addition to a widget collection via appropriate widgets (see the widget controls section on how to do that).
HiCognition implements preprocessing to allow answering three main questions at a genomic region set (see the concept section for more details):
- Exploring average behavior: What is the average magnitude of a specific 1d-/2d-genomic signal?
- Exploring heterogeneity: Is the population of regions homogeneous with respect to a collection of 1d- or 2d-features? What subsets have different behavior with respect to a collection of 1d- or 2d-features?
- Enrichment analysis: What other regions are enriched?
The results of these preprocessing steps can be visualized using specific widgets:
1D-average widget
Allows to assess what the average magnitude of a 1d-genomic signal is at a genomic region set
2D-average widget
Allows to assess what the average magnitude of a 2d-genomic signal is at a genomic region set
Stacked lineprofile widget
Allows to assess whether a population of regions is homogeneous with regards to a 1d-genomic signal
1D-feature embedding widget
Allows to assess whether a population of regions is homogeneous with regards to a set of 1d-genomic signals
2D-feature embedding widget
Allows to assess whether a population of regions is homogeneous with regards to a 2d-genomic signal
Association widget
Allows to assess what other regions overlap with a set of genomic regions