Quality Control of Sequencing Data (fastqcr)
FASTQC’ is the most widely used tool for evaluating the quality of high throughput sequencing data. It produces, for each sample, an html report and a compressed file containing the raw data. If you have hundreds of samples, you are not going to open up each ‘HTML’ page. You need some way of looking at these data in aggregate. ‘fastqcr’ Provides helper functions to easily parse, aggregate and analyze ‘FastQC’ reports for large numbers of samples. It provides a convenient solution for building a ‘Multi-QC’ report, as well as, a ‘one-sample’ report with result interpretations.

Rcpp’ Implementation of ‘FSelector’ Entropy-Based Feature Selection Algorithms with a Sparse Matrix Support (FSelectorRcpp)
Rcpp’ (free of ‘Java’/’Weka’) implementation of ‘FSelector’ entropy-based feature selection algorithms with a sparse matrix support. It is also equipped with a parallel backend.

Ordinal Forests: Prediction and Class Width Inference with Ordinal Target Variables (ordinalForest)
Ordinal forests (OF) are a method for ordinal regression with high-dimensional and low-dimensional data that is able to predict the values of the ordinal target variable for new observations and at the same time estimate the relative widths of the classes of the ordinal target variable. Using a (permutation-based) variable importance measure it is moreover possible to rank the importances of the covariates. OF will be presented in an upcoming technical report by Hornung et al.. The main functions of the package are: ordfor() (construction of OF), predict.ordfor() (prediction of the target variable values of new observations), and plot.ordfor() (visualization of the estimated relative widths of the classes of the ordinal target variable).

Global and Individual Tests for Direct Effects (GLIDE)
Functions evaluate global and individual tests for direct effects in Mendelian randomization studies.

Clp (Coin-or linear programming)’ Plugin for the ‘R’ Optimization Interface (ROI.plugin.clp)
Enhances the R Optimization Infrastructure (ROI) package by registering the COIN-OR Clp open-source solver from the COIN-OR suite <https://…/>. It allows for solving linear programming with continuous objective variables keeping sparse constraints definition.