Hidden Markov Models are useful for modeling sequential data. This package provides several functions implemented in C++ for explaining the algorithms used for Hidden Markov Models (forward, backward, decoding, learning).

This package provides a simple method to extract portions of a vector, matrix, or data.frame. The relative portion size and the way the portion is selected can be chosen.

Statistical methods for analyzing case-control point data. Methods include the ratio of kernel densities, the difference in K Functions, the spatial scan statistic, and q nearest neighbors of cases.

An Optimization Algorithm Applied to Stratification Problem.This function aims at constructing optimal strata with an optimization algorithm based on a global optimisation technique called Biased Random Key Genetic Algorithms.

Perform two types of analysis: 1) checking the goodness-of-fit of tree models to your single-cell gene expression data; and 2) deciding which tree best fits your data.

This package is for analysis of SILAC labeled complexome profiling data. It uses peptide table in tab-delimited format as an input and produces ready-to-use tables and plots.

CRImage provides functionality to process and analyze images, in particular to classify cells in biological images. Furthermore, in the context of tumor images, it provides functionality to calculate tumour cellularity.

This package provides a general framework for the simulation of ChIP-seq data. Although currently focused on nucleosome positioning the package is designed to support different types of experiments.

This package detects statistically significant differences between read enrichment profiles in different ChIP-Seq samples. To take advantage of shape differences it uses Kernel methods (Maximum Mean Discrepancy, MMD).

Smooth quantile normalization is a generalization of quantile normalization, which is average of the two types of assumptions about the data generation process: quantile normalization and quantile normalization between groups.

The Triform algorithm uses model-free statistics to identify peak-like distributions of TF ChIP sequencing reads, taking advantage of an improved peak definition in combination with known profile characteristics.

This is a package for fast Non-negative Matrix Factorization (NMF) with automatic rank-determination for dimension reduction of single-cell data using Seurat, RcppML nmf, SingleCellExperiments and similar.

This package provides auxiliary functions and data sets for "Ecological Models and Data", a book presenting maximum likelihood estimation and related topics for ecologists (ISBN 978-0-691-12522-0).

This package performs score test using saddlepoint approximation to estimate the null distribution. It also prepares summary statistics for meta-analysis and performs meta-analysis to combine multiple association results.

Odds and ends collection miscellania. Extra functionality for slices (.find(), RevSlice), strings and other things. Things in odds may move to more appropriate crates if we find them.

Odds and ends collection miscellania. Extra functionality for slices (.find(), RevSlice), strings and other things. Things in odds may move to more appropriate crates if we find them.

Odds and ends collection miscellania. Extra functionality for slices (.find(), RevSlice), strings and other things. Things in odds may move to more appropriate crates if we find them.

This package provides a collection of functions for computing "r-values" from various kinds of user input such as MCMC output or a list of effect size estimates and associated standard errors. Given a large collection of measurement units, the r-value, r, of a particular unit is a reported percentile that may be interpreted as the smallest percentile at which the unit should be placed in the top r-fraction of units.

Haplotype simulations of rare variant genetic data that emulates real data can be performed with RAREsim. RAREsim uses the expected number of variants in MAC bins - either as provided by default parameters or estimated from target data - and an abundance of rare variants as simulated HAPGEN2 to probabilistically prune variants. RAREsim produces haplotypes that emulate real sequencing data with respect to the total number of variants, allele frequency spectrum, haplotype structure, and variant annotation.

Pure Rust implementation of SHA-3, a family of Keccak-based hash functions including the SHAKE family of eXtendable-Output Functions (XOFs), as well as the accelerated variant TurboSHAKE

Reads Arena <https://www.arenasimulation.com/> CSV output files and generates nice tables and plots. The package contains a Shiny App that can be used to interactively visualize Arena's results.

This package provides a set of R functions and data sets for the book Introduction to Bayesian Statistics, Bolstad, W.M. (2017), John Wiley & Sons ISBN 978-1-118-09156-2.

This package provides functions for Bayesian Data Analysis, with datasets from the book "Bayesian data Analysis (second edition)" by Gelman, Carlin, Stern and Rubin. Not all datasets yet, hopefully completed soon.

Implementation of an efficient BLAST-like sequence comparison algorithm, written in C++11 and using native R datatypes. Blaster is based on nsearch - Schmid et al (2018) <doi:10.1101/399782>.