Title: Shiny Apps for Lateral Flow Assays
Authors@R: c(person("Filip", "Paskali", role = c("aut", "cre"),
person("Weronika", "Schary", role = "aut",
person("Matthias", "Kohl", role = "aut",
Author: Filip Paskali [aut, cre] (<https://orcid.org/0000-0002-9647-6294>),
Description: Shiny apps for the quantitative analysis of images from lateral flow assays (LFAs). The images are segmented and background corrected and color intensities are extracted. The apps can be used to import and export intensity data and to calibrate LFAs by means of linear, loess, or gam models. The calibration models can further be saved and applied to intensity data from new images for determining concentrations.
Imports: stats, utils, graphics, methods, mgcv, shiny, shinyjs,
shinythemes, shinyFiles, shinyMobile (>= 0.9), EBImage, DT,

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

Packaged: 2015-08-06 08:44:27 UTC; martapadilla

Title: Estimating Local False Discovery Rates Using the Method of
Description: Estimation of the local false discovery rate using the method of moments.
Packaged: 2020-11-18 02:52:23 UTC; alikarimnezhad

Title: Estimating Local False Discovery Rates Using Empirical Bayes
Author: Ali Karimnezhad, Johnary Kim, Anna Akpawu, Justin Chitpin and David R Bickel
Description: 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>.
Packaged: 2017-09-27 01:34:32 UTC; a.karimnezhad