Plots empty Lexis grids, adds lifelines and highlights certain areas of the grid, like cohorts and age groups.

An R implementation of the LexRank algorithm described by G. Erkan and D. R. Radev (2004) <DOI:10.1613/jair.1523>.

Provides an extension to factors called 'lfactor' that are similar
    to factors but allows users to refer to 'lfactor' levels by either the level or
    the label.

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.

Ratios of count data such as obtained from RNA-seq are modelled
    using Bayesian statistics to derive posteriors for effects sizes. This
    approach is described in Erhard & Zimmer (2015) <doi:10.1093/nar/gkv696> 
    and Erhard (2018) <doi:10.1093/bioinformatics/bty471>.

Functions for performing and visualizing Local Fisher Discriminant
    Analysis(LFDA), Kernel Fisher Discriminant Analysis(KLFDA), and Semi-supervised
    Local Fisher Discriminant Analysis(SELF).

Suite of R functions for the estimation of the local false discovery rate (LFDR) using Type II maximum likelihood estimation (MLE).

Estimation of the local false discovery rate using the method of moments.

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>.