A generalised data structure for fast and efficient loading and data munching of sparse omics data. The 'OmicFlow' requires an up-front validated metadata template from the user,
    which serves as a guide to connect all the pieces together by aligning them into a single object that is defined as an 'omics' class. 
    Once this unified structure is established, users can perform manual subsetting, visualisation, and statistical analysis, or leverage the automated 'autoFlow' method to generate a comprehensive report.

It provides functions to generate a correlation matrix
    from a genetic dataset and to use this matrix to predict the phenotype of an
    individual by using the phenotypes of the remaining individuals through
    kriging. Kriging is a geostatistical method for optimal prediction or best
    unbiased linear prediction. It consists of predicting the value of a
    variable at an unobserved location as a weighted sum of the variable at
    observed locations. Intuitively, it works as a reverse linear regression:
    instead of computing correlation (univariate regression coefficients are
    simply scaled correlation) between a dependent variable Y and independent
    variables X, it uses known correlation between X and Y to predict Y.

A tool for interactive exploration of the results from 'omics'
  experiments to facilitate novel discoveries from high-throughput biology. The
  software includes R functions for the 'bioinformatician' to deposit study
  metadata and the outputs from statistical analyses (e.g. differential
  expression, enrichment). These results are then exported to an interactive
  JavaScript dashboard that can be interrogated on the user's local machine or
  deployed online to be explored by collaborators. The dashboard includes
  'sortable' tables, interactive plots including network visualization, and
  fine-grained filtering based on statistical significance.

A method for the quantitative prediction using omics data. 
    This package provides functions to construct the quantitative prediction 
    model using omics data.