The package implements an algorithm for fast gene set enrichment analysis. Using the fast algorithm makes more permutations and gets more fine grained p-values, which allows using accurate standard approaches to multiple hypothesis correction.

This package aims to provide a pipeline for the low-level analysis of gene expression microarray data, primarily focused on the Agilent platform, but which also provides utilities which may be useful for other platforms.

This package provides a set of functions to run R code in an environment in which global state has been temporarily modified. Many of these functions were originally a part of the r-devtools package.

This package provides an R-based solution for symbolic differentiation. It admits user-defined functions as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.

This package tests the goodness of fit of a distribution of offspring to the Normal, Poisson, and Gamma distribution and estimates the proportional paternity of the second male (P2) based on the best fit distribution.

This package performs approximate bayesian computation (ABC) model choice and parameter inference via random forests. This machine learning tool named random forests (RF) can conduct selection among the highly complex models covered by ABC algorithms.

Makes it incredibly easy to build interactive web applications with R. Automatic "reactive" binding between inputs and outputs and extensive prebuilt widgets make it possible to build beautiful, responsive, and powerful applications with minimal effort.

RNNoise is a noise suppression library based on a recurrent neural network. The algorithm is described in Jean-Marc Valin's paper A Hybrid DSP/Deep Learning Approach to Real-Time Full-Band Speech Enhancement.

ntpd-rs is a tool for synchronizing your computer's clock, implementing the NTP and NTS protocols. It is written in Rust, with a focus on security and stability. It includes both client and server support.

This package contains functions for the SCENT algorithm. SCENT uses single-cell multimodal data and links ATAC-seq peaks to their target genes by modeling association between chromatin accessibility and gene expression across individual single cells.

The goal of anpan is to consolidate statistical methods for strain analysis. This includes automated filtering of metagenomic functional profiles, testing genetic elements for association with outcomes, phylogenetic association testing, and pathway-level random effects models.

The vegan package provides tools for descriptive community ecology. It has most basic functions of diversity analysis, community ordination and dissimilarity analysis. Most of its multivariate tools can be used for other data types as well.

Piano performs gene set analysis using various statistical methods, from different gene level statistics and a wide range of gene-set collections. The package contains functions for combining the results of multiple runs of gene set analyses.

SAIGE is a package for efficiently controlling for case-control imbalance and sample relatedness in single-variant assoc tests (SAIGE) and controlling for sample relatedness in region-based assoc tests in large cohorts and biobanks (SAIGE-GENE+).

Strex is a collection of string manipulation functions not provided by the stringi or stringr packages. The foremost of these is the extraction of numbers from strings. There are many other handy functionalities in strex.

This is a package for the analysis of music and speech. Analyze music and speech, extract features like MFCCs, handle wave files and their representation in various ways, read MP3, read MIDI, perform steps of a transcription, ...

This package offers an interface to NDEx servers, e.g. the public server at http://ndexbio.org/. It can retrieve and save networks via the API. Networks are offered as RCX object and as igraph representation.

Identify Surface Protein coding genes from a list of candidates. Systematically download data from GEO and TCGA or use your own data. Perform DGE on bulk RNAseq data. Perform Meta-analysis. Descriptive enrichment analysis and plots.

dwm is a dynamic window manager for X. It manages windows in tiled, monocle and floating layouts. All of the layouts can be applied dynamically, optimising the environment for the application in use and the task performed.

User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the StanHeaders package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.

This package implements a variety of low-level analyses of single-cell RNA-seq data. Methods are provided for normalization of cell-specific biases, assignment of cell cycle phase, and detection of highly variable and significantly correlated genes.

BioQC performs quality control of high-throughput expression data based on tissue gene signatures. It can detect tissue heterogeneity in gene expression data. The core algorithm is a Wilcoxon-Mann-Whitney test that is optimised for high performance.

This package provides a method to sample cells from single-cell data. It also generates an aggregate profile on a pruned K-Nearest Neighbor graph. This approach leads to an improved gene expression profile for quantifying gene regulations.

This package provides a means to mock a package function, i.e., temporarily substitute it for testing. It was designed as a drop-in replacement for the now deprecated testthat::with_mock() and testthat::local_mock().