A tool for detecting reversions for a given pathogenic mutation from 
	next-generation DNA sequencing data. It analyses reads aligned to the locus of the 
	pathogenic mutation and reports reversion events where secondary mutations have 
	restored or undone the deleterious effect of the original pathogenic mutation, e.g., 
	secondary indels complement to a frameshift pathogenic mutation converting the 
	orignal frameshift mutation into inframe mutaions, deletions or SNVs that replaced 
	the original pathogenic mutation restoring the open reading frame, SNVs changing the 
	stop codon caused by the original nonsense SNV into an amino acid, etc.

Processes and visualizes the output of complex phylogenetic analyses from the 'RevBayes' phylogenetic graphical modeling software.

Function revgeo() allows you to use the Photon geocoder for OpenStreetMap <http://photon.komoot.de>, Google Maps <http://maps.google.com>, and Bing <https://www.bingmapsportal.com> to reverse geocode coordinate pairs with minimal hassle.

A portable Shiny tool to explore patient-level electronic health record data 
    and perform chart review in a single integrated framework. This tool supports 
    browsing clinical data in many different formats including multiple versions 
    of the 'OMOP' common data model as well as the 'MIMIC-III' data model. In 
    addition, chart review information is captured and stored securely via the 
    Shiny interface in a 'REDCap' (Research Electronic Data Capture) project 
    using the 'REDCap' API. See the 'ReviewR' website for additional information, 
    documentation, and examples.

Tools to (i) check consistency of a finite set of consumer demand observations with a number of revealed preference axioms at a given efficiency level, (ii) compute goodness-of-fit indices when the data do not obey the axioms, and (iii) compute power against uniformly random behavior.

We visualize the standard deviation of a data set as the radius of a cylinder whose volume equals the total volume of several cylinders made by revolving the empirical cumulative distribution function about the vertical line through the mean. For more details see Sarkar and Rashid (2016) <doi:10.1080/00031305.2016.1165734>.