MASS, graphics, stats,igraph,clusterGeneration,Matrix,Biobase,
methods, ggplot2

Tools for processing data after a Genome Wide Association Study
Designed for analysis of the results of a Genome Wide Association Study. Includes tools to pull lists of Chromosome number and SNP position below a certain significance threshold, refine gene networks (including data I/O for Cytoscape), and check SNP base pair changes.

c(person("Rebecca", "Steorts", email= "beka@stat.duke.edu", role=c("aut", "cre")), person("Andee", "Kaplan", email= "andrea.kaplan@duke.edu", role="aut"), person("Srini", "Sunil", email="srinivas.sunil@duke.edu", role="aut"))
Duplicated publication data (pre-processed and formatted) for entity resolution. This data set contains a total of 1879 records. The following variables are included in the data set: id, title, book title, authors, address, date, year, editor, journal, volume, pages, publisher, institution, type, tech, note. The data set has a respective gold data set that provides information on which records match based on id.
Rebecca Steorts [aut, cre],
Andee Kaplan [aut],
Srini Sunil [aut]

Apply 'colorffy' Color Gradients Within 'shiny' Elements
c(person(given = "Mohamed El Fodil",
family = "Ihaddaden",
role = c("aut", "cre"),
email = "ihaddaden.fodeil@gmail.com"),
person(given = "Hadjer",
family = "Haned",
email = "Haned.hadjer.enssea@gmaail.com",
role = c("ctb")))
Allows the user to apply nice color gradients to 'shiny' elements.
The gradients are extracted from the 'colorffy' website. See <https://www.colorffy.com/gradients/catalog>.
Mohamed El Fodil Ihaddaden [aut, cre],
Hadjer Haned [ctb]

Perform a correlational class analysis of the data, resulting in a partition of the data into separate modules.

Generate correlated count random variables
Generate high-dimensional correlated count random variables with a prespecified Pearson correlation.

Generate high-dimensional correlated count random
variables with a prespecified Pearson correlation.

Community Estimation in G-Models via CORD
Xi (Rossi) LUO, Florentina Bunea, Christophe Giraud
Partition data points (variables) into communities/clusters, similar to clustering algorithms, such as k-means and hierarchical clustering.  This package implements a clustering algorithm based on a new metric CORD, defined for high dimensional parametric or semi-parametric distributions.  Read http://arxiv.org/abs/1508.01939 for more details.