Doubly robust average partial effect estimation. This implementation contains methods for adding additional smoothness to plug-in regression procedures and for estimating score functions using smoothing splines. Details of the method can be found in Harvey Klyne and Rajen D. Shah (2023) <arXiv:2308.09207>.

Creation and use of R Repositories via helper functions 
 to insert packages into a repository, and to add repository information 
 to the current R session. Two primary types of repositories are support:
 gh-pages at GitHub, as well as local repositories on either the same machine
 or a local network. Drat is a recursive acronym: Drat R Archive Template.

A set of user-friendly wrapper functions for creating consistent graphics and diagrams with lines, common shapes, text, and page settings.
  Compatible with and based on the R 'grid' package.

An interactive image editing tool that can be added as part of the HTML in Shiny,
    R markdown or any type of HTML document. Often times, plots, photos are embedded
    in the web application/file. 'drawer' can take screenshots of these image-like elements, or 
    any part of the HTML document and send to an image editing space called 'canvas' to allow users 
    immediately edit the screenshot(s) within the same document. Users can quickly 
    combine, compare different screenshots, upload their own images 
    and maybe make a scientific figure.

We present DRaWR, a network-based method for ranking genes or
    properties related to a given gene set. Such related genes or properties are
    identified from among the nodes of a large, heterogeneous network of biological
    information. Our method involves a random walk with restarts, performed on
    an initial network with multiple node and edge types, preserving more of the
    original, specific property information than current methods that operate
    on homogeneous networks. In this first stage of our algorithm, we find the
    properties that are the most relevant to the given gene set and extract a
    subnetwork of the original network, comprising only the relevant properties. We
    then rerank genes by their similarity to the given gene set, based on a second
    random walk with restarts, performed on the above subnetwork.