This is a package for estimation of a sparse inverse covariance matrix using a lasso (L1) penalty. Facilities are provided for estimates along a path of values for the regularization parameter.

Graphical and tabular effect displays, e.g., of interactions, for various statistical models with linear predictors.

This package provides an implementation of Adaptive Base Error Model in Ultra-deep Sequencing data (ABEMUS), which combines platform-specific genetic knowledge and empirical signal to readily detect and quantify somatic single nucleotide variants (SNVs) in circulating cell free DNA (cfDNA).

This package provides an R interface to the jExcel library to create web-based interactive tables and spreadsheets compatible with spreadsheet software.

This package performs search for the global minimum of a very complex non-linear objective function with a very large number of optima.

This package provides bitmapped vectors of booleans (no NAs), coercion from and to logicals, integers and integer subscripts, fast boolean operators and fast summary statistics. With bit class vectors of true binary booleans, TRUE and FALSE can be stored with 1 bit only.

The objective of this package is to perform inference using an expressive statistical grammar that coheres with the Tidy design framework.

This package implements the R version of the log4j package. It offers hierarchic loggers, multiple handlers per logger, level based filtering, space handling in messages and custom formatting.

Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via the Template Model Builder. Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.

This package provides a smooth mapping of multidimensional points into low-dimensional space defined by a self-organizing map. It is designed to work with FlowSOM and flow-cytometry use-cases.

This package provides a comprehensive implementation of dynamic time warping (DTW) algorithms in R. DTW computes the optimal (least cumulative distance) alignment between points of two time series. Common DTW variants covered include local (slope) and global (window) constraints, subsequence matches, arbitrary distance definitions, normalizations, minimum variance matching, and so on.

Phylogenetic trees generally contain multiple components including nodes, edges, branches and associated data. This package provides an approach to convert tree objects to tidy data frames. It also provides tidy interfaces to manipulate tree data.

This package lets you interact with Google Sheets through the Sheets API v4. This package can read and write both the metadata and the cell data in a Sheet.

This package provides syntax highlighting for R source code. Currently it supports LaTeX and HTML output. Source code of other languages is supported via Andre Simon's highlight package.

In order to reduce potential package dependencies and conflicts, generics provides a number of commonly used S3 generics that are not provided by base R methods related to model fitting.

This package provides procedures to create preliminary exploratory data visualisations of an entire dataset to identify problems or unexpected features using ggplot2.

This is a package to compare sequence fragment lengths or molecular weights from pairs of lanes. The number of matching bands in the Restriction Fragment Length Polymorphism (RFLP) data is calculated using the align-and-count method.

This package provides grid grobs that fill in a user-defined area with various patterns. It includes enhanced versions of the geometric and image-based patterns originally contained in the ggpattern package as well as original pch, polygon_tiling, regular_polygon, rose, text, wave, and weave patterns plus support for custom user-defined patterns.

This is a package to read raw accelerometry from GT3X+ accelerometry data and plain table data to calculate the Activity Index from Bai et al. (2016) doi:10.1371/journal.pone.0160644.

Feature Selection with Regularized Random Forest. This package is based on the randomForest package by Andy Liaw. The key difference is the RRF() function that builds a regularized random forest. Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener, Regularized random forest for classification by Houtao Deng, Regularized random forest for regression by Xin Guan. Reference: Houtao Deng (2013) <doi:10.48550/arXiv.1306.0237>.

This package provides the Molecular Signatures Database (MSigDB) gene sets typically used with the Gene Set Enrichment Analysis (GSEA) software in a standard R data frame with key-value pairs. Included are the original human gene symbols and Entrez IDs as well as the equivalents for various frequently studied model organisms such as mouse, rat, pig, fly, and yeast.

This is a package containing Public Key Infrastructure functions such as verifying certificates, RSA encryption and signing, which can be used to build PKI infrastructure and perform cryptographic tasks.

This package allows the user to specify debug messages as special string constants, and control debugging of packages via environment variables.

This package converts between R and Simple Feature sf objects, without depending on the Simple Feature library. Conversion functions are available at both the R level, and through Rcpp.