Documentations

Training and Analysis functions

These functions are used for training and analysis

  • sPipeline
    Function to setup the pipeline for completing ab initio training given the input data
  • sHexGrid
    Function to define a supra-hexagonal grid
  • sHexGridVariant
    Function to define a variant of a supra-hexagonal grid
  • sHexPolygon
    Function to extract polygon location per hexagon within a supra-hexagonal grid
  • sTopology
    Function to define the topology of a map grid
  • sInitial
    Function to initialise a sInit object given a topology and input data
  • sTrainology
    Function to define trainology (training environment)
  • sTrainSeq
    Function to implement training via sequential algorithm
  • sTrainBatch
    Function to implement training via batch algorithm
  • sBMH
    Function to identify the best-matching hexagons/rectangles for the input data
  • sNeighDirect
    Function to calculate direct neighbors for each hexagon/rectangle in a grid
  • sNeighAny
    Function to calculate any neighbors for each hexagon/rectangle in a grid
  • sHexDist
    Function to calculate distances between hexagons/rectangles in a 2D grid
  • sDistance
    Function to compute the pairwise distance for a given data matrix
  • sDmat
    Function to calculate distance matrix in high-dimensional input space but according to neighborhood relationships in 2D output space
  • sDmatMinima
    Function to identify local minima (in 2D output space) of distance matrix (in high-dimensional input space)
  • sDmatCluster
    Function to partition a grid map into clusters
  • sCompReorder
    Function to reorder component planes
  • sWriteData
    Function to write out the best-matching hexagons and/or cluster bases in terms of data
  • sMapOverlay
    Function to overlay additional data onto the trained map for viewing the distribution of that additional data

Visualisation functions

These functions are used for visualisation

  • visHexPattern
    Function to visualise codebook matrix or input patterns within a supra-hexagonal grid
  • visHexGrid
    Function to visualise a supra-hexagonal grid
  • visHexMapping
    Function to visualise various mapping items within a supra-hexagonal grid
  • visHexBarplot
    Function to visualise codebook matrix using barplot for all hexagons or a specific one
  • visHexComp
    Function to visualise a component plane of a supra-hexagonal grid
  • visColormap
    Function to define a colormap
  • visColoralpha
    Function to add transparent (alpha) into colors
  • visColorbar
    Function to define a colorbar
  • visVp
    Function to create viewports for multiple supra-hexagonal grids
  • visHexMulComp
    Function to visualise multiple component planes of a supra-hexagonal grid
  • visHexAnimate
    Function to animate multiple component planes of a supra-hexagonal grid
  • visCompReorder
    Function to visualise multiple component planes reorded within a sheet-shape rectangle grid
  • visDmatCluster
    Function to visualise clusters/bases partitioned from a supra-hexagonal grid
  • visDmatHeatmap
    Function to visualise gene clusters/bases partitioned from a supra-hexagonal grid using heatmap
  • visKernels
    Function to visualize neighborhood kernels
  • visHeatmap
    Function to visualise input data matrix using heatmap
  • visHeatmapAdv
    Function to visualise input data matrix using advanced heatmap
  • visTreeBootstrap
    Function to build and visualise the bootstrapped tree
  • visTreeBSclust
    Function to obtain clusters from a bootstrapped tree

Built-in datasets

  • Fang(Fang.sampleinfo, Fang.geneinfo)
    Human embryo gene expression dataset from Fang et al. (2010)
  • Golub
    Leukemia gene expression dataset from Golub et al. (1999)
  • Xiang
    Arabidopsis embryo gene expression dataset from Xiang et al.