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r-micropan
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public |
A collection of functions for computations and visualizations of microbial pan-genomes.
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2025-09-24 |
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r-cnogpro
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public |
Methods for assigning copy number states and breakpoints in resequencing experiments of prokaryotic organisms.
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2025-09-24 |
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r-tnet
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public |
Binary ties limit the richness of network analyses as relations are unique. The two-mode structure contains a number of features lost when projection it to a one-mode network. Longitudinal datasets allow for an understanding of the causal relationship among ties, which is not the case in cross-sectional datasets as ties are dependent upon each other.
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2025-09-24 |
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r-sybil
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public |
This Systems Biology Package (Gelius-Dietrich et. al. (2012) <doi:10.1186/1752-0509-7-125>) implements algorithms for constraint based analyses of metabolic networks, e.g. flux-balance analysis (FBA), minimization of metabolic adjustment (MOMA), regulatory on/off minimization (ROOM), robustness analysis and flux variability analysis. The package is easily extendable for additional algorithms. Most of the current LP/MILP solvers are supported via additional packages.
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2025-09-24 |
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r-highcharter
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A wrapper for the 'Highcharts' library including shortcut functions to plot R objects. 'Highcharts' <http://www.highcharts.com/> is a charting library offering numerous chart types with a simple configuration syntax.
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2025-09-24 |
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yarn
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public |
Fast, reliable, and secure dependency management.
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2025-09-24 |
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r-rmcfs
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MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) is a Monte Carlo method-based tool for feature selection. It also allows for the discovery of interdependencies between the relevant features. MCFS-ID is particularly suitable for the analysis of high-dimensional, 'small n large p' transactional and biological data. M. Draminski, J. Koronacki (2018) <doi:10.18637/jss.v085.i12>.
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2025-09-24 |
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r-ggflowchart
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Flowcharts can be a useful way to visualise complex processes. This package uses the layered grammar of graphics of 'ggplot2' to create simple flowcharts.
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2025-09-24 |
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r-ggm
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Functions and datasets for maximum likelihood fitting of some classes of graphical Markov models.
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2025-09-24 |
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r-smotefamily
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A collection of various oversampling techniques developed from SMOTE is provided. SMOTE is a oversampling technique which synthesizes a new minority instance between a pair of one minority instance and one of its K nearest neighbor. (see <https://www.jair.org/media/953/live-953-2037-jair.pdf> for more information) Other techniques adopt this concept with other criteria in order to generate balanced dataset for class imbalance problem.
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2025-09-24 |
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qe
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public |
QUANTUM ESPRESSO (opEn-Source Package for Research in Electronic Structure, Simulation, and Optimization)
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2025-09-24 |
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r-c3net
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public |
This package allows inferring gene regulatory networks with direct physical interactions from microarray expression data using C3NET.
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2025-09-24 |
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pygeogrids
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public |
Creation and handling of Discrete Global Grids or Point collections.
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2025-09-24 |
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pixi-build-api-version
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public |
The protocol version for pixi build backends.
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2025-09-24 |
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r-discretecdalgorithm
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public |
Structure learning of Bayesian network using coordinate-descent algorithm. This algorithm is designed for discrete network assuming a multinomial data set, and we use a multi-logit model to do the regression. The algorithm is described in Gu, Fu and Zhou (2016) <arXiv:1403.2310>.
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2025-09-24 |
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r-bipartite
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public |
Functions to visualise webs and calculate a series of indices commonly used to describe pattern in (ecological) webs. It focuses on webs consisting of only two levels (bipartite), e.g. pollination webs or predator-prey-webs. Visualisation is important to get an idea of what we are actually looking at, while the indices summarise different aspects of the web's topology.
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2025-09-24 |
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r-bdgraph
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public |
Statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi and Wit (2019) <doi:10.18637/jss.v089.i03>.
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2025-09-24 |
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r-seqnet
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public |
Methods to generate random gene-gene association networks and simulate RNA-seq data from them, as described in Grimes and Datta (2021) <doi:10.18637/jss.v098.i12>. Includes functions to generate random networks of any size and perturb them to obtain differential networks. Network objects are built from individual, overlapping modules that represent pathways. The resulting network has various topological properties that are characteristic of gene regulatory networks. RNA-seq data can be generated such that the association among gene expression profiles reflect the underlying network. A reference RNA-seq dataset can be provided to model realistic marginal distributions. Plotting functions are available to visualize a network, compare two networks, and compare the expression of two genes across multiple networks.
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2025-09-24 |
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r-biganalytics
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public |
Extend the 'bigmemory' package with various analytics. Functions 'bigkmeans' and 'binit' may also be used with native R objects. For 'tapply'-like functions, the bigtabulate package may also be helpful. For linear algebra support, see 'bigalgebra'. For mutex (locking) support for advanced shared-memory usage, see 'synchronicity'.
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2025-09-24 |
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r-huge
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public |
Provides a general framework for high-dimensional undirected graph estimation. It integrates data preprocessing, neighborhood screening, graph estimation, and model selection techniques into a pipeline. In preprocessing stage, the nonparanormal(npn) transformation is applied to help relax the normality assumption. In the graph estimation stage, the graph structure is estimated by Meinshausen-Buhlmann graph estimation or the graphical lasso, and both methods can be further accelerated by the lossy screening rule preselecting the neighborhood of each variable by correlation thresholding. We target on high-dimensional data analysis usually d >> n, and the computation is memory-optimized using the sparse matrix output. We also provide a computationally efficient approach, correlation thresholding graph estimation. Three regularization/thresholding parameter selection methods are included in this package: (1)stability approach for regularization selection (2) rotation information criterion (3) extended Bayesian information criterion which is only available for the graphical lasso.
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2025-09-24 |
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r-alakazam
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public |
Provides methods for high-throughput adaptive immune receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In particular, immunoglobulin (Ig) sequence lineage reconstruction, lineage topology analysis, diversity profiling, amino acid property analysis and gene usage. Citations: Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>, Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.
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2025-09-24 |
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r-ecodist
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Dissimilarity-based analysis functions including ordination and Mantel test functions, intended for use with spatial and community data.
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2025-09-24 |
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r-tidygraph
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public |
A graph, while not "tidy" in itself, can be thought of as two tidy data frames describing node and edge data respectively. 'tidygraph' provides an approach to manipulate these two virtual data frames using the API defined in the 'dplyr' package, as well as provides tidy interfaces to a lot of common graph algorithms.
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2025-09-24 |
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r-qgraph
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Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.
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2025-09-24 |
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r-intergraph
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Functions implemented in this package allow to coerce (i.e. convert) network data between classes provided by other R packages. Currently supported classes are those defined in packages: network and igraph.
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2025-09-24 |
