Introduction

supraHex is an open-source package for tabular omics data analysis using a supra-hexagonal map. The supra-hexagonal map is a giant hexagon on a 2-dimensional map grid seamlessly consisting of smaller hexagons. It intends to meet the need for quickly understanding genome-wide biological data, which usually involve a large number of genomic coordinates (e.g. genes) but a much smaller number of samples.

supraHex first uses a supra-hexagonal map to self-organise the input omics data, and then post-analyses the trained map for integrated tasks: simultaneous analysis of genes and samples, and multilayer omics data comparisons.

supraHex aims to deliver an eye-intuitive tool and a dedicated website with extensive online documentation and easy-to-follow demos.

Features

  • An integrated framework for the ultrafast understanding of any tabular omics data, both scientifically and artistically
  • The supra-hexagonal map trained via a self-organising learning algorithm
  • Visualisations at and across nodes of the map
  • Partitioning of the map into gene meta-clusters
  • Sample correlation on 2D sample landscape
  • Overlaying additional data onto the trained map for exploring relationships between input and additional data
  • Support for heatmap and tree building and visualisations
  • This package can run on Windows, Mac and Linux

Workflow

Manual

  • supraHex User Manual (PDF, Rnw)
  • supraHex Reference Manual (PDF, HTML)

Demos

URL

Dependency

  • Depends: hexbin
  • Imports: ape, MASS
  • Suggests:
  • Extends:

License

GPL-2

Author

Hai Fang and Julian Gough