Title: Microbiome Regression-Based Analysis Tests
Authors@R: c(person("Anna", "Plantinga", role = c("aut", "cre"), email = "amp9@williams.edu"),
person("Nehemiah", "Wilson", role = c("aut", "ctb")),
person("Haotian", "Zheng", role = c("aut", "ctb")),
person("Xiang", "Zhan", role = c("aut", "ctb")),
person("Ni", "Zhao", role = c("aut", "ctb")),
Description: Test for overall association between microbiome composition data and phenotypes via phylogenetic kernels.
The phenotype can be univariate continuous or binary (Zhao et al. (2015) <doi:10.1016/j.ajhg.2015.04.003>),
multivariate (Zhan et al. (2017) <doi:10.1002/gepi.22030>) and
structured phenotypes (Zhan et al. (2017) <doi:10.1111/biom.12684>).
The package can also use robust and quantile regression (Fu et al. (2020+), in preparation).
In each case, the microbiome community effect is modeled nonparametrically through a kernel function,
which can incorporate phylogenetic tree information.
Imports: MASS, CompQuadForm, quantreg, GUniFrac, PearsonDS, lme4,
Matrix, permute, mixtools, survival, ecodist, stats
Suggests: knitr, propr, cluster, dirmult, vegan, rmarkdown, tidyverse,

Matrix, permute, mixtools, survival, stats

person("Hongjiao", "Liu", role = c("aut", "ctb")))
The package can also use robust and quantile regression (unpublished work).

person("Tianying", "Wang", role = c("aut", "ctb")),
Description: Test for overall association between microbiome composition data
and phenotypes via phylogenetic kernels. The phenotype can be univariate
continuous or binary (Zhao et al. (2015) <doi:10.1016/j.ajhg.2015.04.003>),
The package can also use robust regression (unpublished work) and
integrated quantile regression (Wang et al. (2021) <doi:10.1093/bioinformatics/btab668>).
In each case, the microbiome community effect is modeled nonparametrically
through a kernel function, which can incorporate phylogenetic tree information.

Suggests: knitr, vegan, rmarkdown, tidyverse, kableExtra

Title: MiRNA Quality Control and Diagnosis
Description: A set of functions to carry out quality control, training and classification analyses on datasets containing MiRNA multiplets. The package implements the method introduced in Ricci et al. (2015) <doi:10.1186/s12859-015-0715-9>.
person("Michele", "Castelluzzo", email = "michele.castelluzzo@unitn.it", role = "aut"),
person("Alessio", "Perinelli", email = "alessio.perinelli@unitn.it", role = "cre"),
person("Simone", "Detassis", role = "aut"),
person("Michela Alessandra", "Denti", email = "michela.denti@unitn.it", role = "aut"),
person("Leonardo", "Ricci", email = "leonardo.ricci@unitn.it", role = "aut"))