Adaptive Association Tests for Multiple Phenotypes using
Proportional Odds Model (POM-aSPU)
POM-aSPU test evaluates an association between an ordinal response and multiple phenotypes, for details see Kim and Pan (2017) <DOI:10.1002/gepi.22033>.

Plot demographic graphs for single/multiple populations from coalescent simulation program input. Currently, this package can support the 'ms', 'msHot', 'MaCS', 'msprime', 'SCRM', and 'Cosi2' simulation programs. It does not check the simulation program input for correctness, but assumes the simulation program input has been validated by the simulation program. More features will be added to this package in the future, please check the 'GitHub' page for the latest updates: <https://github.com/YingZhou001/POPdemog>.

Power Simulation for Sequential Analysis and Multiple Hypotheses
c(person("Gáspár", "Lukács", email = "lkcsgaspar@gmail.com", role =
c("aut", "cre")))
Calculates, via simulation, power and appropriate "stopping"
alpha boundaries (and/or futility bounds) for sequential analyses (i.e.,
"group sequential design") as well as for multiple hypotheses (multiple tests
included in an analysis), given any specified global error rate. This enables
the sequential use of practically any significance test, as long as the
underlying data can be simulated in advance to a reasonable approximation.
testthat (>= 3.0.0), faux, knitr, rmarkdown

Power Simulation for Sequential Analyses and Multiple Hypotheses
Calculates, via simulation, power and appropriate stopping
alpha boundaries (and/or futility bounds) for sequential analyses (i.e.,
group sequential design) as well as for multiple hypotheses (multiple tests
included in an analysis), given any specified global error rate. This enables
the sequential use of practically any significance test, as long as the
underlying data can be simulated in advance to a reasonable approximation.

Phylogeny-Guided OTU-Specific Association Test for Microbiome
Data
c(person("Caizhi", "Huang", role = "aut"),
person("Jung-Ying", "Tzeng", role = "aut"),
person("Shannon", "Holloway", role = c("aut", "cre"),
email = "sthollow@ncsu.edu"))
Caizhi Huang [aut],
Jung-Ying Tzeng [aut],
Shannon Holloway [aut, cre]
Implements the Phylogeny-Guided Microbiome OTU-Specific Association
Test method, which boosts the testing power by adaptively borrowing
information from phylogenetically close OTUs (operational taxonomic units)
of the target OTU. This method
is built on a kernel machine regression framework and allows for flexible
modeling of complex microbiome effects, adjustments for covariates, and
can accommodate both continuous and binary outcomes.
'ACAT.R' 'CKAT.R' 'POSTmData.R' 'distanceMatrix.R'
'getKernel.R' 'glmFit.R' 'lmFit.R' 'p.adjust.POST.R'
'plot.POST.R' 'post.R' 'print.POST.R'