Description: A molecular genetics tool that processes binary data from fragment analysis. It consolidates replicate sample pairs, outputs summary statistics, and produces hierarchical clustering trees and nMDS plots. This package was developed from the publication available here: <https://www.sciencedirect.com/science/article/pii/S1049964420306538>. The GUI version of this package is available on the R Shiny online server at: <https://clarkevansteenderen.shinyapps.io/BINMAT/> or it is accessible via GitHub by typing: shiny::runGitHub("BinMat", "clarkevansteenderen") into the console in R. Two real-world datasets accompany the package: an AFLP dataset of Bunias orientalis samples from Tewes et. al. (2017) <https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/1365-2745.12869>, and an ISSR dataset of Nymphaea specimens from Reid et. al. (2021) <https://www.sciencedirect.com/science/article/pii/S0304377021000218> . The authors of these publications are thanked for allowing the use of their data.
Imports: pvclust (>= 2.0), MASS (>= 7.3), stats (>= 3.4.0), graphics

Title: Data Generation with Binary and Continuous Non-normal Components
Description: Generation of multiple binary and continuous non-normal variables simultaneously
given the marginal characteristics and association structure based on the methodology

Title: Data Generation with Binary and Continuous Non-Normal Components

Author: Gul Inan, Hakan Demirtas, Ran Gao
proposed by Demirtas et al. (2012) <DOI:10.1002/sim.5362>.

Title: Simultaneous generation of multivariate binary and normal
Depends: mvtnorm, corpcor, psych, Matrix
Description: Generating multiple binary and normal variables simultaneously given marginal characteristics and association structure based on the methodology proposed by Demirtas and Doganay (2012).

Description: Generating multiple binary and normal variables
simultaneously given marginal characteristics and association
structure based on the methodology proposed by Demirtas and

Title: Simultaneous Generation of Multivariate Binary and Normal