This package provides functionality for performing divergence analysis as presented in Dinalankara et al, "Digitizing omics profiles by divergence from a baseline", PANS 2018. This allows the user to simplify high dimensional omics data into a binary or ternary format which encapsulates how the data is divergent from a specified baseline group with the same univariate or multivariate features.

This package allows to estimate missing values in DNA methylation data. methyLImp method is based on linear regression since methylation levels show a high degree of inter-sample correlation. Implementation is parallelised over chromosomes since probes on different chromosomes are usually independent. Mini-batch approach to reduce the runtime in case of large number of samples is available.

Efficiently access the Bedrock Bio library of open-access computational biology datasets. Lazily query datasets backed by DuckDB and Apache Iceberg', with support for predicate pushdown and column projection to the cloud storage backend. This enables quick, iterative access to otherwise massive, unwieldy datasets without downloading them in full. See <https://bedrock.bio> for available datasets and documentation.

This package implements several algorithms for bundling edges in networks and flow and metro map layouts. This includes force directed edge bundling <doi:10.1111/j.1467-8659.2009.01450.x>, a flow algorithm based on Steiner trees<doi:10.1080/15230406.2018.1437359> and a multicriteria optimization method for metro map layouts <doi:10.1109/TVCG.2010.24>.

This package provides a collection of functions that would help one to build features based on external data. Very useful for Data Scientists in data to day work. Many functions create features using parallel computation. Since the nitty gritty of parallel computation is hidden under the hood, the user need not worry about creating clusters and shutting them down.

This package provides an interface to the system-level grep utility for efficiently reading, filtering, and aggregating data from multiple flat files. By pre-filtering data at the command line before it enters the R environment, the package reduces memory overhead and improves ingestion speed. Includes functions for counting records across large file systems and supports recursive directory searching.

R lists, especially nested lists, can be very difficult to visualize or represent. Sometimes str() is not enough, so this suite of htmlwidgets is designed to help see, understand, and maybe even modify your R lists. The function reactjson() requires a package reactR that can be installed from CRAN or <https://github.com/timelyportfolio/reactR>.

Efficient calculation of pseudo-ranks and (pseudo)-rank based test statistics. In case of equal sample sizes, pseudo-ranks and mid-ranks are equal. When used for inference mid-ranks may lead to paradoxical results. Pseudo-ranks are in general not affected by such a problem. See Happ et al. (2020, <doi:10.18637/jss.v095.c01>) for details.

Contract helpers built with S7 for expressing runtime protocols around ordinary S7 dispatch. Structural interfaces describe small sets of required S7 generics, while explicit traits record registered implementations with optional default methods and associated metadata. Optional runtime checks can validate argument and return specifications in contract-scoped evaluation. Generative laws combine generators, deterministic shrinking, and one-result tinytest expectations.

For biparental, three and four-way crosses Identity by Descent (IBD) probabilities can be calculated using Hidden Markov Models and inheritance vectors following Lander and Green (<https://www.jstor.org/stable/29713>) and Huang (<doi:10.1073/pnas.1100465108>). One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris.

This package provides bindings to Tree-sitter', an incremental parsing system for programming tools. Tree-sitter builds concrete syntax trees for source files of any language, and can efficiently update those syntax trees as the source file is edited. It also includes a robust error recovery system that provides useful parse results even in the presence of syntax errors.

Create dense vector representation of words and documents using quanteda'. Implements Word2vec (Mikolov et al., 2013) <doi:10.48550/arXiv.1310.4546>, Doc2vec (Le & Mikolov, 2014) <doi:10.48550/arXiv.1405.4053> and Latent Semantic Analysis (Deerwester et al., 1990) <doi:10.1002/(SICI)1097-4571(199009)41:6%3C391::AID-ASI1%3E3.0.CO;2-9>.

Computes confidence intervals for nonlinear functions of model parameters (e.g., product of k coefficients) in single-level and multilevel structural equation models. Methods include the distribution of the product, Monte Carlo simulation, and bootstrap methods. It also performs the Model-Based Constrained Optimization (MBCO) procedure for hypothesis testing of indirect effects. References: Tofighi, D., and MacKinnon, D. P. (2011). RMediation: An R package for mediation analysis confidence intervals. Behavior Research Methods, 43, 692-700. <doi:10.3758/s13428-011-0076-x>; Tofighi, D., and Kelley, K. (2020). Improved inference in mediation analysis: Introducing the model-based constrained optimization procedure. Psychological Methods, 25(4), 496-515. <doi:10.1037/met0000259>; Tofighi, D. (2020). Bootstrap Model-Based Constrained Optimization Tests of Indirect Effects. Frontiers in Psychology, 10, 2989. <doi:10.3389/fpsyg.2019.02989>.

Psupertime is supervised pseudotime for single cell RNAseq data. It uses single cell RNAseq data, where the cells have a known ordering. This ordering helps to identify a small number of genes which place cells in that known order. It can be used for discovery of relevant genes, for identification of subpopulations, and characterization of further unknown or differently labelled data.

Supplies AnnotationHub with MassBank metabolite/compound annotations bundled in CompDb SQLite databases. CompDb SQLite databases contain general compound annotation as well as fragment spectra representing fragmentation patterns of compounds ions. MassBank data is retrieved from https://massbank.eu/MassBank and processed using helper functions from the CompoundDb Bioconductor package into redistributable SQLite databases.

The CompensAID is an automated quality control tool, which determines for each marker combination in the FCS file, whether there a potential presence of reference errors. Such reference errors, which represent themselves in the form of skewed populations, are detected by integrating the Secondary Stain Index (SSI) score. Marker combinations with an SSI < 1 are flagged by CompensAID.

The package provides statistical tools for detecting differentially abundant proteins in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling. It provides multiple functionalities, including aata visualization, protein quantification and normalization, and statistical modeling and inference. Furthermore, it is inter-operable with other data processing tools, such as Proteome Discoverer, MaxQuant, OpenMS and SpectroMine.

spatialFDA is a package to calculate spatial statistics metrics. The package takes a SpatialExperiment object and calculates spatial statistics metrics using the package spatstat. Then it compares the resulting functions across samples/conditions using functional additive models as implemented in the package refund. Furthermore, it provides exploratory visualisations using functional principal component analysis, as well implemented in refund.

Estimate group aggregates, where one can set user-defined conditions that each group of records must satisfy to be suitable for aggregation. If a group of records is not suitable, it is expanded using a collapsing scheme defined by the user. A paper on this package was published in the Journal of Statistical Software <doi:10.18637/jss.v112.i04>.

This package contains a range of functions covering the present development of the distributional method for the dichotomisation of continuous outcomes. The method provides estimates with standard error of a comparison of proportions (difference, odds ratio and risk ratio) derived, with similar precision, from a comparison of means. See the URL below or <arXiv:1809.03279> for more information.

This package implements the G-Formula method for causal inference with time-varying treatments and confounders using Bayesian multiple imputation methods, as described by Bartlett et al (2025) <doi:10.1177/09622802251316971>. It creates multiple synthetic imputed datasets under treatment regimes of interest using the mice package. These can then be analysed using rules developed for analysing multiple synthetic datasets.

Support for geostatistical analysis of multivariate data, in particular data with restrictions, e.g. positive amounts, compositions, distributional data, microstructural data, etc. It includes descriptive analysis and modelling for such data, both from a two-point Gaussian perspective and multipoint perspective. The methods mainly follow Tolosana-Delgado, Mueller and van den Boogaart (2018) <doi:10.1007/s11004-018-9769-3>.

This package provides a suite of tools for literature-based discovery in biomedical research. Provides functions for retrieving scientific articles from PubMed and other NCBI databases, extracting biomedical entities (diseases, drugs, genes, etc.), building co-occurrence networks, and applying various discovery models including ABC', AnC', LSI', and BITOLA'. The package also includes visualization tools for exploring discovered connections.

Life and Fertility Tables are appropriate to study the dynamics of arthropods populations. This package provides utilities for constructing Life Tables and Fertility Tables, related demographic parameters, and some simple graphs of interest. It also offers functions to transform the obtained data into a known format for better manipulation. In addition, two methods for obtaining the confidence interval are included.