Title: Haplotype Two Snips Out of a Paired Group of Patients
Description: Two unordered pairs of data of two different snips positions is haplotyped by resolving a small number ob closed equations.

Title: Comparison of Alternative Multiple Sequence Alignments
Description: Methods for comparing two alternative multiple
sequence alignments (MSAs) to determine whether they align homologous residues in
the same columns as one another. It then classifies similarities and differences
into conserved gaps, conserved sequence, merges, splits or shifts of one MSA relative
to the other. Summarising these categories for each MSA column yields information
on which sequence regions are agreed upon my both MSAs, and which differ. Several
plotting functions enable easily visualisation of the comparison data for analysis.
Imports: Rcpp (>= 0.11.6), seqinr, ggplot2, reshape2

Title: Comparison of Alternative Multiple Aequence Alignments

Imports: Rcpp (>= 0.11.6), seqinr, ggplot2, reshape2, tools, utils

Title: Computes all of a word's possible spellings.
Description: Contains functions possSpells.fnc and

Author: Antoine Tremblay, IWK Health Center

Title: Allele Retention, Inbreeding, and Demography
Description: Simulate the effect of management or demography on allele
retention and inbreeding accumulation in bottlenecked
populations of animals with overlapping generations.

Description: Simulate the effect of management or demography on allele retention and inbreeding accumulation in bottlenecked populations of animals with overlapping generations.

Title: Predict and Visualize Population-Level Changes in Allele
Frequencies in Response to Climate Change
Author: Roeland Kindt [cre, aut] (<https://orcid.org/0000-0002-7672-0712>)
Description: Methods (Kindt, R. 2021. <doi:10.1101/2021.01.15.426775>) are provided of calibrating and predicting shifts in allele frequencies through redundancy analysis ('vegan::rda()') and generalized additive models ('mgcv::gam()'). Visualization functions for predicted changes in allele frequencies include 'shift.dot.ggplot()', 'shift.pie.ggplot()', 'shift.moon.ggplot()', 'shift.waffle.ggplot()' and 'shift.surf.ggplot()' that are made with input data sets that are prepared by helper functions for each visualization method. Examples in the documentation show how to prepare animated climate change graphics through a time series with the 'gganimate' package. Function 'amova.rda()' shows how Analysis of Molecular Variance can be directly conducted with the results from redundancy analysis.
Imports: vegan (>= 2.5-6), BiodiversityR (>= 2.12-3), adegenet
Suggests: poppr, mgcv, dplyr, ggplot2, GGally, ggforce, ggrepel, ggsci,