Methods for performing genetic risk
        prediction from genotype data.  You can use it to perform risk
        prediction for individuals, or for families with missing data.

Create interactive manhattan, Q-Q and volcano plots that are usable from the R console, 
    in 'Dash' apps, in the 'RStudio' viewer pane, in 'R Markdown' documents, and in 'Shiny' apps.
    Hover the mouse pointer over a point to show details or drag a rectangle to
    zoom. A manhattan plot is a popular graphical method for visualizing results
    from high-dimensional data analysis such as a (epi)genome wide association study
    (GWAS or EWAS), in which p-values, Z-scores, test statistics are plotted on a scatter
    plot against their genomic position. Manhattan plots are used for visualizing
    potential regions of interest in the genome that are associated with a phenotype.
    Interactive manhattan plots allow the inspection of specific value (e.g. rs number or
    gene name) by hovering the mouse over a cell, as well as zooming into a region of the
    genome (e.g. a chromosome) by dragging a rectangle around the relevant area.
    This work is based on the 'qqman' package and the 'plotly.js'
    engine. It produces similar manhattan and Q-Q plots as the 'manhattan' and 'qq'
    functions in the 'qqman' package, with the advantage of including extra annotation 
    information and interactive web-based visualizations directly from R. 
    Once uploaded to a 'plotly' account, 'plotly' graphs (and the data behind them) 
    can be viewed and modified in a web browser.

This plot integrates annotation into a manhattan plot. The plot is implemented as a heatmap, which is binned using -log10(p-value) and chromosome position. Annotation currently supported is minor allele frequency and gene function high impact variants.

Provides access to coded election programmes from the Manifesto
    Corpus and to the Manifesto Project's Main Dataset and routines to analyse this
    data. The Manifesto Project <https://manifesto-project.wzb.eu> collects and
    analyses election programmes across time and space to measure the political
    preferences of parties. The Manifesto Corpus contains the collected and
    annotated election programmes in the Corpus format of the package 'tm' to enable
    easy use of text processing and text mining functionality. Specific functions
    for scaling of coded political texts are included.