Package: supraHex 1.45.1

Hai Fang

supraHex: supraHex: a supra-hexagonal map for analysing tabular omics data

A supra-hexagonal map is a giant hexagon on a 2-dimensional grid seamlessly consisting of smaller hexagons. It is supposed to train, analyse and visualise a high-dimensional omics input data. The supraHex is able to carry out gene clustering/meta-clustering and sample correlation, plus intuitive visualisations to facilitate exploratory analysis. More importantly, it allows for overlaying additional data onto the trained map to explore relations between input and additional data. So with supraHex, it is also possible to carry out multilayer omics data comparisons. Newly added utilities are advanced heatmap visualisation and tree-based analysis of sample relationships. Uniquely to this package, users can ultrafastly understand any tabular omics data, both scientifically and artistically, especially in a sample-specific fashion but without loss of information on large genes.

Authors:Hai Fang and Julian Gough

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supraHex.pdf |supraHex.html✨
supraHex/json (API)
NEWS

# Install 'supraHex' in R:
install.packages('supraHex', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://r-forge.r-project.org/projects/suprahex

Datasets:
  • Fang - Human embryo gene expression dataset from Fang et al.
  • Golub - Leukemia gene expression dataset from Golub et al.
  • Xiang - Arabidopsis embryo gene expression dataset from Xiang et al.

On BioConductor:supraHex-1.45.0(bioc 3.21)supraHex-1.43.0(bioc 3.20)

softwareclusteringvisualizationgeneexpression

3.73 score 20 scripts 746 downloads 9 mentions 39 exports 40 dependencies

Last updated 3 days agofrom:ca523d2e02. Checks:ERROR: 7. Indexed: yes.

TargetResultDate
Doc / VignettesFAILDec 18 2024
R-4.5-winERRORDec 18 2024
R-4.5-linuxERRORDec 18 2024
R-4.4-winERRORDec 18 2024
R-4.4-macERRORDec 18 2024
R-4.3-winERRORDec 18 2024
R-4.3-macERRORDec 18 2024

Exports:sBMHsCompReordersDistancesDmatsDmatClustersDmatMinimasHexDistsHexGridsHexGridVariantsHexPolygonsInitialsMapOverlaysNeighAnysNeighDirectsPipelinesTopologysTrainBatchsTrainologysTrainSeqsWriteDatavisColoralphavisColorbarvisColormapvisCompReordervisDmatClustervisDmatHeatmapvisHeatmapvisHeatmapAdvvisHexAnimatevisHexBarplotvisHexCompvisHexGridvisHexMappingvisHexMulCompvisHexPatternvisKernelsvisTreeBootstrapvisTreeBSclustvisVp

Dependencies:apebitbit64clicliprcpp11crayondigestdplyrfansigenericsgluehexbinhmsigraphlatticelifecyclemagrittrMASSMatrixnlmepillarpkgconfigprettyunitsprogresspurrrR6Rcppreadrrlangstringistringrtibbletidyrtidyselecttzdbutf8vctrsvroomwithr

Readme and manuals

Help Manual

Help pageTopics
Human embryo gene expression dataset from Fang et al. (2010)Fang Fang.geneinfo Fang.sampleinfo
Leukemia gene expression dataset from Golub et al. (1999)Golub
Function to identify the best-matching hexagons/rectangles for the input datasBMH
Function to reorder component planessCompReorder
Function to compute the pairwise distance for a given data matrixsDistance
Function to calculate distance matrix in high-dimensional input space but according to neighborhood relationships in 2D output spacesDmat
Function to partition a grid map into clusterssDmatCluster
Function to identify local minima (in 2D output space) of distance matrix (in high-dimensional input space)sDmatMinima
Function to calculate distances between hexagons/rectangles in a 2D gridsHexDist
Function to define a supra-hexagonal gridsHexGrid
Function to define a variant of a supra-hexagonal gridsHexGridVariant
Function to extract polygon location per hexagon within a supra-hexagonal gridsHexPolygon
Function to initialise a sInit object given a topology and input datasInitial
Function to overlay additional data onto the trained map for viewing the distribution of that additional datasMapOverlay
Function to calculate any neighbors for each hexagon/rectangle in a gridsNeighAny
Function to calculate direct neighbors for each hexagon/rectangle in a gridsNeighDirect
Function to setup the pipeline for completing ab initio training given the input datasPipeline
Function to define the topology of a map gridsTopology
Function to implement training via batch algorithmsTrainBatch
Function to define trainology (training environment)sTrainology
Function to implement training via sequential algorithmsTrainSeq
Function to write out the best-matching hexagons and/or cluster bases in terms of datasWriteData
Function to add transparent (alpha) into colorsvisColoralpha
Function to define a colorbarvisColorbar
Function to define a colormapvisColormap
Function to visualise multiple component planes reorded within a sheet-shape rectangle gridvisCompReorder
Function to visualise clusters/bases partitioned from a supra-hexagonal gridvisDmatCluster
Function to visualise gene clusters/bases partitioned from a supra-hexagonal grid using heatmapvisDmatHeatmap
Function to visualise input data matrix using heatmapvisHeatmap
Function to visualise input data matrix using advanced heatmapvisHeatmapAdv
Function to animate multiple component planes of a supra-hexagonal gridvisHexAnimate
Function to visualise codebook matrix using barplot for all hexagons or a specific onevisHexBarplot
Function to visualise a component plane of a supra-hexagonal gridvisHexComp
Function to visualise a supra-hexagonal gridvisHexGrid
Function to visualise various mapping items within a supra-hexagonal gridvisHexMapping
Function to visualise multiple component planes of a supra-hexagonal gridvisHexMulComp
Function to visualise codebook matrix or input patterns within a supra-hexagonal gridvisHexPattern
Function to visualize neighborhood kernelsvisKernels
Function to build and visualise the bootstrapped treevisTreeBootstrap
Function to obtain clusters from a bootstrapped treevisTreeBSclust
Function to create viewports for multiple supra-hexagonal gridsvisVp
Arabidopsis embryo gene expression dataset from Xiang et al. (2011)Xiang