c(person("Filip", "Paskali", role = c("aut", "cre"),
email = "F.Paskali@hs-furtwangen.de"),
person("Weronika", "Schary", role = "aut",
email = "W.Schary@hs-furtwangen.de",
comment = c(ORCID = "0000-0002-7229-316X")),
person("Matthias", "Kohl", role = "aut",
email = "Matthias.Kohl@stamats.de",
comment = c(ORCID = "0000-0001-9514-8910")))
Filip Paskali [aut, cre],
Weronika Schary [aut] (<https://orcid.org/0000-0002-7229-316X>),
Matthias Kohl [aut] (<https://orcid.org/0000-0001-9514-8910>)

Estimation of the Local False Discovery Rates by Type II Maximum
Likelihood Estimation
Ye Yang, Marta Padilla, Alaa Ali, Kyle Leckett, Zhenyu Yang, Zuojing Li, Corey M. Yanofsky and David R. Bickel
Suite of R functions for the estimation of the local false discovery rate (LFDR) using Type II maximum likelihood estimation (MLE).

Estimating Local False Discovery Rates Using the Method of
Moments
Estimation of the local false discovery rate using the method of moments.

Estimating Local False Discovery Rates Using Empirical Bayes
Methods
Ali Karimnezhad, Johnary Kim, Anna Akpawu, Justin Chitpin and David R Bickel
New empirical Bayes methods aiming at analyzing the association of single nucleotide polymorphisms (SNPs) to some particular disease are implemented in this package. The package uses local false discovery rate (LFDR) estimates of SNPs within a sample population defined as a  "reference class" and discovers if SNPs are associated with the corresponding disease. Although SNPs are used throughout this document, other biological data such as protein data and other gene data can be used. Karimnezhad, Ali and Bickel, D. R. (2016) <http://hdl.handle.net/10393/34889>.

Tests for Genetic Association/Gene-Environment Interaction in
Longitudinal Gene-Environment-Wide Interaction Studies
Zihuai He, Seunggeun Lee, Bhramar Mukherjee, Min Zhang
Functions for testing the genetic association/gene-environment interaction in longitudinal gene-environment-wide interaction studies. Generalized score type tests are used for set based analyses. Then GEE based score tests are applied to all single variants within the defined set.