Imports: XML, sf, raster, terra, stars, tools, utils, rgdal, foreign,
Suggests: dplyr, testthat (>= 3.0.0), covr

Description: Contains functions that are useful for pre- and post-processing the tree output from the MCMC-based C++ program sampletrees. The program sampletrees is used to sample gene genealogies conditional on either phased or unphased SNP genotype data. More information about sampletrees can be found at http://stat.sfu.ca/statgen/research/sampletrees.html . Pre-processing tasks involve creating the settings file, the haplotype estimation files (if input data is genotype), and error checking the settings. Post-processing involves reading in the MCMC output from a run of sampletrees and computing summary statistics.
Author: Kelly Burkett, Brad McNeney, Jinko Graham
Packaged: 2015-02-02 18:50:40 UTC; kellyburkett

Title: MCMC Sampling of Gene Genealogies Conditional on Genetic Data
Author: Kelly Burkett, Brad McNeney, Jinko Graham, Jean-Francois Lefebvre
Description: Sample ancestral trees conditional on phased or unphased SNP genotype data. The actual tree sampling is done using a C++ program that is launched within R. The package also contains functions for specifying the tree-sampling settings (pre-processing) and for storing and manipulating the sampled trees (post-processing). More information about 'sampletrees' can be found at <http://stat.sfu.ca/statgen/research/sampletrees.html>.
Imports: Rcpp (>= 0.12.9), haplo.stats, ape

Packaged: 2018-01-03 16:56:49 UTC; kellyburkett

Packaged: 2020-02-21 18:07:31 UTC; kellyburkett

Title: Ports the Workflow of "Resampling Stats" Add-in to R
person("Paulo", "Prado", , "prado@ib.usp.br", role = c("aut", "cre")),
person("Andr\'e", "Chalom", , "andrechalom@gmail.com", role = c("aut")),
person("Alexandre", "Oliveira", , "adalardo@usp.br", role = c("aut"))
Description: Resampling Stats (http://www.resample.com) is an add-in for
running randomization tests in Excel worksheets. The workflow is (1) to define
a statistic of interest that can be calculated from a data table, (2) to
randomize rows ad/or columns of a data table to simulate a null hypothesis
and (3) and to score the value of the statistic from many randomizations. The
relative frequency distribution of the statistic in the simulations is then
used to infer the probability of the observed value be generated by the null
process (probability of Type I error). This package intends to translate this
logic for R for teaching purposes. Keeping the original workflow is favored over