An implementation of list comprehensions as purely syntactic sugar with a minor runtime overhead. It constructs nested for-loops and executes the byte-compiled loops to collect the results.

Subset a control group to match an intervention group on a set of features using multivariate matching and propensity score calipers. Based on methods in Rosenbaum and Rubin (1985).

Basic functions for microbial sequence data analysis. The idea is to use generic R data structures as much as possible, making R data wrangling possible also for sequence data.

Helps to create ggplot2 charts in the style used by the National Road Safety Observatory (ONSV). The package includes functions to customize ggplot2 objects with new theme and colors.

Perform scale linking to establish relationships between instruments that measure similar constructs according to the PROsetta Stone methodology, as in Choi, Schalet, Cook, & Cella (2014) <doi:10.1037/a0035768>.

This package provides access to the latest Amazon Mechanical Turk ('MTurk') <https://www.mturk.com> Requester API (version 2017â 01â 17'), replacing the now deprecated MTurkR package.

Includes functions to calculate several physicochemical properties and indices for amino-acid sequences as well as to read and plot XVG output files from the GROMACS molecular dynamics package.

This takes in a series of multi-layer raster files and returns a phenology projection raster, following methodologies described in John (2016) <https://etda.libraries.psu.edu/catalog/13521clj5135>.

This package provides a collection of tools for approximating the PDQ functions (respectively, the cumulative distribution, density, and quantile) of probability distributions via classical expansions involving moments and cumulants.

An R wrapper for pulling data from the Spotify Web API <https://developer.spotify.com/documentation/web-api/> in bulk, or post items on a Spotify user's playlist.

This package contains various ggplot2 themes and color palettes based on TV shows such as Game of Thrones', Brooklyn Nine-Nine', Avatar: The Last Airbender', Spongebob Squarepants', and more.

When a package is loaded, the source repository is checked for new versions and a message is shown in the console indicating whether the package is out of date.

Parse entire folders of non-rectangular xlsx files into a single rectangular and tidy data.frame based on a custom template file defining the column names of the output.

The package contains functions to perform normalization of high-throughput qPCR data. Basic functions for processing raw Ct data plus functions to generate diagnostic plots are also available.

This is a package that can be used for quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets.

This is an R package for pre-processing of flow and mass cytometry data. This package includes panel editing or renaming for FCS files, bead-based normalization and debarcoding.

This package contains the core survival analysis routines, including definition of Surv objects, Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models, and parametric accelerated failure time models.

This package provides a command line parser inspired by Python's optparse library to be used with Rscript to write shebang scripts that accept short and long options.

This library provides a datatype which can be interpreted by apply-refact. It exists as a separate library so that applications can specify refactorings without depending on GHC.

This package provides a utility library intended at providing configurable reader macros for common tasks such as accessors, hash-tables, sets, uiop:run-program, arrays and a few others.

This gem makes mathematical operations more precise in Ruby and integrates other mathematical standard libraries. Prior to Ruby 2.5, mathn was part of the Ruby standard library.

This gem is a library that provides trigonometric and transcendental functions for complex numbers. The functions in this module accept integers, floating-point numbers or complex numbers as arguments.

Software to perform supervised and pixel based raster image classification. It has been designed to facilitate land-cover analysis. Five classification algorithms can be used: Maximum Likelihood Classification, Multinomial Logistic Regression, Neural Networks, Random Forests and Support Vector Machines. The output includes the classified raster and standard classification accuracy assessment such as the accuracy matrix, the overall accuracy and the kappa coefficient. An option for in-sample verification is available.

This package provides functions for conducting robust variance estimation (RVE) meta-regression using both large and small sample RVE estimators under various weighting schemes. These methods are distribution free and provide valid point estimates, standard errors and hypothesis tests even when the degree and structure of dependence between effect sizes is unknown. Also included are functions for conducting sensitivity analyses under correlated effects weighting and producing RVE-based forest plots.