Description: This package provides tools for the identification of unique of multilocus genotypes when both genotyping error and missing data may be present. The package is targeted at those working with large datasets and databases containing multiple samples of each individual, a situation that is common in conservation genetics, and particularly in non-invasive wildlife sampling applications. Functions explicitly incorporate missing data, and can tolerate allele mismatches created by genotyping error. If you use this tool, please cite the package using the journal article in Molecular Ecology Resources (Galpern et al., 2012).  Please use citation('allelematch') to find this. Due to changing CRAN policy, and the size and compile time of the vignettes, they can no longer be distributed with this package.  Please contact the package primary author, or visit the allelematch site for a complete vignette (http://nricaribou.cc.umanitoba.ca/allelematch/).  For users with access to academic literature, tutorial material is also available as supplementary material to the article describing this software.

Title: A fast, unbiased and exact allelic exact test
Description: This is the implementation in R+C of a new association
test described in "A fast, unbiased and exact allelic exact
test for case-control association studies" (Submitted).  It
appears that in most cases the classical chi-square test used
for testing for allelic association on genotype data is biased.
Our test is unbiased, exact but fast throught careful
Packaged: Wed May 24 03:02:01 2006; kforner

Authors@R: person("Zhiqiang", "Wang", email = "zhiqiang.wang@menzies.edu.au", role = c("aut", "cre"))
Description: Estimates and plots effect estimates from models with all possible
combinations of a list of variables. It can be used for assessing treatment
effects in clinical trials or risk factors in bio-medical and epidemiological
research. Like Stata command 'confall' (Wang Z (2007) <doi:10.1177/1536867X0700700203> ),
'allestimates' calculates and stores all effect estimates, and plots them against p values or
Akaike information criterion (AIC) values. It currently has functions for linear
regression: all_lm(), logistic and Poisson regression: all_glm() and all_speedglm(),
and Cox proportional hazards regression: all_cox().
Imports: broom, ggplot2, MASS, speedglm, survival, tibble, tidyr,