A Scheme runtime compiler.

Use Pry as your rails console

An efficient implementation of an lru cache

Fast Implementation of Gruber's Markdown in C

RnBeads annotation package for the assembly hg38.

Turns nested lists into data.frames in an orderly manner.

Automatically generated RnBeads annotation package for the assembly mm10.

This package provides a collection of compression filters for use with HDF5 datasets.

Agilent annotation data (chip rgug4105a) assembled using data from public repositories.

Superclasses PostgreSQL connection to help enable full dplyr functionality on Redshift'.

Redcarpet is an extensible Ruby library for Markdown processing and conversion to (X)HTML.

Agilent Rat annotation data (chip rgug4130a) assembled using data from public repositories.

This package is an automatically generated RnBeads annotation package for the assembly hg19.

This gem extends ruby-rdf with several common RDF vocabularies.

Agilent "Rat Genome, Whole" annotation data (chip rgug4131a) assembled using data from public repositories.

Genome wide annotation for Rat, primarily based on mapping using Entrez Gene identifiers.

Convert REDCap exports into tidy tables for easy handling of REDCap repeat instruments and event arms.

Generates graphs, CSV files, and coordinates related to river valleys when calling the riverbuilder() function.

MCMC based sampling of binary matrices with fixed margins as used in exact Rasch model tests.

Carrying out inferences about any linear combination of proportions and the ratio of two proportions.

This package provides tools for filtering occurrence records, generating alpha-hull-derived range polygons and mapping species distributions.

This package provides the headers and static library of Protocol buffers for other R packages to compile and link against.

This package provides color schemes for maps (and other graphics) designed by Cynthia Brewer as described at http://colorbrewer2.org

This package provides fast machine learning algorithms including matrix factorization and divisive clustering for large sparse and dense matrices.