R-universe search: modular

igraph

igraph:Network Analysis and Visualization

Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.

Maintained by Kirill Müller. Last updated 13 hours ago.

complex-networks graph-algorithms graph-theory mathematics network-analysis network-graph fortran libxml2 glpk openblas cpp

8.3 match 582 stars 21.11 score 31k scripts 1.9k dependents

geomorphr

geomorph:Geometric Morphometric Analyses of 2D and 3D Landmark Data

Read, manipulate, and digitize landmark data, generate shape variables via Procrustes analysis for points, curves and surfaces, perform shape analyses, and provide graphical depictions of shapes and patterns of shape variation.

Maintained by Dean Adams. Last updated 1 months ago.

9.7 match 76 stars 12.05 score 700 scripts 6 dependents

bioc

netZooR:Unified methods for the inference and analysis of gene regulatory networks

netZooR unifies the implementations of several Network Zoo methods (netzoo, netzoo.github.io) into a single package by creating interfaces between network inference and network analysis methods. Currently, the package has 3 methods for network inference including PANDA and its optimized implementation OTTER (network reconstruction using mutliple lines of biological evidence), LIONESS (single-sample network inference), and EGRET (genotype-specific networks). Network analysis methods include CONDOR (community detection), ALPACA (differential community detection), CRANE (significance estimation of differential modules), MONSTER (estimation of network transition states). In addition, YARN allows to process gene expresssion data for tissue-specific analyses and SAMBAR infers missing mutation data based on pathway information.

Maintained by Tara Eicher. Last updated 9 days ago.

networkinference network generegulation geneexpression transcription microarray graphandnetwork gene-regulatory-network transcription-factors

11.6 match 105 stars 7.98 score

leifeld

btergm:Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood

Temporal Exponential Random Graph Models (TERGM) estimated by maximum pseudolikelihood with bootstrapped confidence intervals or Markov Chain Monte Carlo maximum likelihood. Goodness of fit assessment for ERGMs, TERGMs, and SAOMs. Micro-level interpretation of ERGMs and TERGMs. The methods are described in Leifeld, Cranmer and Desmarais (2018), JStatSoft <doi:10.18637/jss.v083.i06>.

Maintained by Philip Leifeld. Last updated 12 months ago.

complex-networks dynamic-analysis ergm estimation goodness-of-fit inference longitudinal-data network-analysis prediction tergm

13.5 match 17 stars 6.70 score 83 scripts 2 dependents

bioc

mistyR:Multiview Intercellular SpaTial modeling framework

mistyR is an implementation of the Multiview Intercellular SpaTialmodeling framework (MISTy). MISTy is an explainable machine learning framework for knowledge extraction and analysis of single-cell, highly multiplexed, spatially resolved data. MISTy facilitates an in-depth understanding of marker interactions by profiling the intra- and intercellular relationships. MISTy is a flexible framework able to process a custom number of views. Each of these views can describe a different spatial context, i.e., define a relationship among the observed expressions of the markers, such as intracellular regulation or paracrine regulation, but also, the views can also capture cell-type specific relationships, capture relations between functional footprints or focus on relations between different anatomical regions. Each MISTy view is considered as a potential source of variability in the measured marker expressions. Each MISTy view is then analyzed for its contribution to the total expression of each marker and is explained in terms of the interactions with other measurements that led to the observed contribution.

Maintained by Jovan Tanevski. Last updated 5 months ago.

software biomedicalinformatics cellbiology systemsbiology regression decisiontree singlecell spatial bioconductor biology intercellular machine-learning modular molecular-biology multiview spatial-transcriptomics

11.0 match 51 stars 7.87 score 160 scripts

timcdlucas

EMMLi:A Maximum Likelihood Approach to the Analysis of Modularity

Fit models of modularity to morphological landmarks. Perform model selection on results. Fit models with a single within-module correlation or with separate within-module correlations fitted to each module.

Maintained by Tim Lucas. Last updated 8 years ago.

modularity morphometrics paeleobiology

19.0 match 2 stars 4.00 score 9 scripts

cran

PSIndependenceTest:Independence Tests for Two-Way, Three-Way and Four-Way Contingency Tables

Presentation two independence tests for two-way, three-way and four-way contingency tables. These tests are: the modular test and the logarithmic minimum test. For details on this method see: Sulewski (2017) <doi:10.18778/0208-6018.330.04>, Sulewski (2018) <doi:10.1080/02664763.2018.1424122>, Sulewski (2019) <doi:10.2478/bile-2019-0003>, Sulewski (2021) <doi:10.1080/00949655.2021.1908286>.

Maintained by Piotr Sulewski. Last updated 2 years ago.

21.1 match 2.70 score 5 scripts

pharmaverse

datacutr:SDTM Datacut

Supports the process of applying a cut to Standard Data Tabulation Model (SDTM), as part of the analysis of specific points in time of the data, normally as part of investigation into clinical trials. The functions support different approaches of cutting to the different domains of SDTM normally observed.

Maintained by Tim Barnett. Last updated 1 months ago.

7.1 match 14 stars 7.48 score 11 scripts

pik-piam

gms:'GAMS' Modularization Support Package

A collection of tools to create, use and maintain modularized model code written in the modeling language 'GAMS' (<https://www.gams.com/>). Out-of-the-box 'GAMS' does not come with support for modularized model code. This package provides the tools necessary to convert a standard 'GAMS' model to a modularized one by introducing a modularized code structure together with a naming convention which emulates local environments. In addition, this package provides tools to monitor the compliance of the model code with modular coding guidelines.

Maintained by Jan Philipp Dietrich. Last updated 4 days ago.

6.0 match 1 stars 8.73 score 414 scripts 37 dependents

klmr

box:Write Reusable, Composable and Modular R Code

A modern module system for R. Organise code into hierarchical, composable, reusable modules, and use it effortlessly across projects via a flexible, declarative dependency loading syntax.

Maintained by Konrad Rudolph. Last updated 13 days ago.

modules packages

4.2 match 888 stars 12.39 score 47 scripts 4 dependents

lem-usp

evolqg:Evolutionary Quantitative Genetics

Provides functions for covariance matrix comparisons, estimation of repeatabilities in measurements and matrices, and general evolutionary quantitative genetics tools. Melo D, Garcia G, Hubbe A, Assis A P, Marroig G. (2016) <doi:10.12688/f1000research.7082.3>.

Maintained by Diogo Melo. Last updated 11 months ago.

openblas cpp

7.8 match 10 stars 6.26 score 114 scripts

ready4-dev

ready4:Develop and Use Modular Health Economic Models

A template model module, tools to help find model modules derived from this template and a programming syntax to use these modules in health economic analyses. These elements are the foundation for a prototype software framework for developing living and transferable models and using those models in reproducible health economic analyses. The software framework is extended by other R libraries. For detailed documentation about the framework and how to use it visit <https://www.ready4-dev.com/>. For a background to the methodological issues that the framework is attempting to help solve, see Hamilton et al. (2024) <doi:10.1007/s40273-024-01378-8>.

Maintained by Matthew Hamilton. Last updated 4 months ago.

computational-modeling health-economics software-framework

7.2 match 2 stars 6.84 score 95 scripts

predictiveecology

quickPlot:A System of Plotting Optimized for Speed and Modularity

A high-level plotting system, compatible with `ggplot2` objects, maps from `sf`, `terra`, `raster`, `sp`. It is built primarily on the 'grid' package. The objective of the package is to provide a plotting system that is built for speed and modularity. This is useful for quick visualizations when testing code and for plotting multiple figures to the same device from independent sources that may be independent of one another (i.e., different function or modules the create the visualizations). The suggested package 'fastshp' can be installed from the repository (<https://PredictiveEcology.r-universe.dev>).

Maintained by Eliot J B McIntire. Last updated 4 months ago.

plotting visualization

5.5 match 6 stars 7.92 score 121 scripts 12 dependents

wallaceecomod

wallace:A Modular Platform for Reproducible Modeling of Species Niches and Distributions

The 'shiny' application Wallace is a modular platform for reproducible modeling of species niches and distributions. Wallace guides users through a complete analysis, from the acquisition of species occurrence and environmental data to visualizing model predictions on an interactive map, thus bundling complex workflows into a single, streamlined interface. An extensive vignette, which guides users through most package functionality can be found on the package's GitHub Pages website: <https://wallaceecomod.github.io/wallace/articles/tutorial-v2.html>.

Maintained by Mary E. Blair. Last updated 9 days ago.

openjdk

5.1 match 133 stars 8.36 score 96 scripts

bioc

NetSAM:Network Seriation And Modularization

The NetSAM (Network Seriation and Modularization) package takes an edge-list representation of a weighted or unweighted network as an input, performs network seriation and modularization analysis, and generates as files that can be used as an input for the one-dimensional network visualization tool NetGestalt (http://www.netgestalt.org) or other network analysis. The NetSAM package can also generate correlation network (e.g. co-expression network) based on the input matrix data, perform seriation and modularization analysis for the correlation network and calculate the associations between the sample features and modules or identify the associated GO terms for the modules.

Maintained by Zhiao Shi. Last updated 5 months ago.

11.3 match 3.60 score 1 scripts

paballand

EconGeo:Computing Key Indicators of the Spatial Distribution of Economic Activities

Functions to compute a series of indices commonly used in the fields of economic geography, economic complexity, and evolutionary economics to describe the location, distribution, spatial organization, structure, and complexity of economic activities. Functions include basic spatial indicators such as the location quotient, the Krugman specialization index, the Herfindahl or the Shannon entropy indices but also more advanced functions to compute different forms of normalized relatedness between economic activities or network-based measures of economic complexity. Most of the functions use matrix calculus and are based on bipartite (incidence) matrices consisting of region - industry pairs.

Maintained by Pierre-Alexandre Balland. Last updated 2 years ago.

7.8 match 41 stars 4.96 score 44 scripts

hfgolino

EGAnet:Exploratory Graph Analysis – a Framework for Estimating the Number of Dimensions in Multivariate Data using Network Psychometrics

Implements the Exploratory Graph Analysis (EGA) framework for dimensionality and psychometric assessment. EGA estimates the number of dimensions in psychological data using network estimation methods and community detection algorithms. A bootstrap method is provided to assess the stability of dimensions and items. Fit is evaluated using the Entropy Fit family of indices. Unique Variable Analysis evaluates the extent to which items are locally dependent (or redundant). Network loadings provide similar information to factor loadings and can be used to compute network scores. A bootstrap and permutation approach are available to assess configural and metric invariance. Hierarchical structures can be detected using Hierarchical EGA. Time series and intensive longitudinal data can be analyzed using Dynamic EGA, supporting individual, group, and population level assessments.

Maintained by Hudson Golino. Last updated 9 days ago.

4.9 match 47 stars 7.80 score 61 scripts 1 dependents

hwborchers

numbers:Number-Theoretic Functions

Provides number-theoretic functions for factorization, prime numbers, twin primes, primitive roots, modular logarithm and inverses, extended GCD, Farey series and continued fractions. Includes Legendre and Jacobi symbols, some divisor functions, Euler's Phi function, etc.

Maintained by Hans W. Borchers. Last updated 2 years ago.

6.3 match 2 stars 6.02 score 370 scripts 70 dependents

lme4

lme4:Linear Mixed-Effects Models using 'Eigen' and S4

Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

Maintained by Ben Bolker. Last updated 3 days ago.

cpp

1.8 match 647 stars 20.69 score 35k scripts 1.5k dependents

evanbiederstedt

dendsort:Modular Leaf Ordering Methods for Dendrogram Nodes

An implementation of functions to optimize ordering of nodes in a dendrogram, without affecting the meaning of the dendrogram. A dendrogram can be sorted based on the average distance of subtrees, or based on the smallest distance value. These sorting methods improve readability and interpretability of tree structure, especially for tasks such as comparison of different distance measures or linkage types and identification of tight clusters and outliers. As a result, it also introduces more meaningful reordering for a coupled heatmap visualization. This method is described in "dendsort: modular leaf ordering methods for dendrogram representations in R", F1000Research 2014, 3: 177 <doi:10.12688/f1000research.4784.1>.

Maintained by Evan Biederstedt. Last updated 4 years ago.

5.2 match 4 stars 7.01 score 472 scripts 3 dependents

johncoene

echarts4r:Create Interactive Graphs with 'Echarts JavaScript' Version 5

Easily create interactive charts by leveraging the 'Echarts Javascript' library which includes 36 chart types, themes, 'Shiny' proxies and animations.

Maintained by David Munoz Tord. Last updated 3 days ago.

echarts hacktoberfest htmlwidget htmlwidgets visualization

3.0 match 603 stars 11.45 score 1.3k scripts 11 dependents

refunders

refund.shiny:Interactive Plotting for Functional Data Analyses

Produces Shiny applications for different types of popular functional data analyses. The functional data analyses are implemented in the refund package, then refund.shiny reads in the refund object and implements an object-specific set of plots based on the object class using S3.

Maintained by Julia Wrobel. Last updated 1 years ago.

6.9 match 4 stars 4.91 score 45 scripts

dgkf

ggpackets:Package Plot Layers for Easier Portability and Modularization

Create groups of 'ggplot2' layers that can be easily migrated from one plot to another, reducing redundant code and improving the ability to format many plots that draw from the same source 'ggpacket' layers.

Maintained by Doug Kelkhoff. Last updated 14 days ago.

ggplot plotting

4.6 match 69 stars 7.34 score 12 scripts 1 dependents

bioc

bluster:Clustering Algorithms for Bioconductor

Wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.

Maintained by Aaron Lun. Last updated 5 months ago.

immunooncology software geneexpression transcriptomics singlecell clustering cpp

3.3 match 9.43 score 636 scripts 51 dependents

stouffer

rnetcarto:Fast Network Modularity and Roles Computation by Simulated Annealing (Rgraph C Library Wrapper for R)

Provides functions to compute the modularity and modularity-related roles in networks. It is a wrapper around the rgraph library (Guimera & Amaral, 2005, <doi:10.1038/nature03288>).

Maintained by Daniel B. Stouffer. Last updated 2 years ago.

gsl

6.7 match 1 stars 4.58 score 38 scripts

kharchenkolab

conos:Clustering on Network of Samples

Wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. 'Conos' focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes. This package interacts with data available through the 'conosPanel' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/conos>. The size of the 'conosPanel' package is approximately 12 MB.

Maintained by Evan Biederstedt. Last updated 1 years ago.

batch-correction scrna-seq single-cell-rna-seq openblas cpp openmp

4.1 match 204 stars 7.32 score 258 scripts

biocro

BioCro:Modular Crop Growth Simulations

A cross-platform representation of models as sets of equations that facilitates modularity in model building and allows users to harness modern techniques for numerical integration and data visualization. Documentation is provided by several vignettes included in this package; also see Lochocki et al. (2022) <doi:10.1093/insilicoplants/diac003>.

Maintained by Justin M. McGrath. Last updated 9 days ago.

cpp

3.6 match 45 stars 8.09 score 81 scripts

glmmtmb

glmmTMB:Generalized Linear Mixed Models using Template Model Builder

Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.

Maintained by Mollie Brooks. Last updated 12 days ago.

cpp openmp

1.8 match 312 stars 16.77 score 3.7k scripts 24 dependents

jakobbossek

grapherator:A Modular Multi-Step Graph Generator

Set of functions for step-wise generation of (weighted) graphs. Aimed for research in the field of single- and multi-objective combinatorial optimization. Graphs are generated adding nodes, edges and weights. Each step may be repeated multiple times with different predefined and custom generators resulting in high flexibility regarding the graph topology and structure of edge weights.

Maintained by Jakob Bossek. Last updated 3 years ago.

combinatorial-optimization graph-generator minimum-spanning-tree multi-objective-optimization optimization

4.8 match 9 stars 6.04 score 27 scripts 1 dependents

rich-iannone

DiagrammeR:Graph/Network Visualization

Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges.

Maintained by Richard Iannone. Last updated 2 months ago.

graph graph-functions network-graph property-graph visualization

1.8 match 1.7k stars 15.18 score 3.8k scripts 87 dependents

vdorie

blme:Bayesian Linear Mixed-Effects Models

Maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting, implementing the methods of Chung, et al. (2013) <doi:10.1007/s11336-013-9328-2>. Extends package 'lme4' (Bates, Maechler, Bolker, and Walker (2015) <doi:10.18637/jss.v067.i01>).

Maintained by Vincent Dorie. Last updated 16 days ago.

3.0 match 43 stars 9.11 score 193 scripts 5 dependents

bioc

BioNAR:Biological Network Analysis in R

the R package BioNAR, developed to step by step analysis of PPI network. The aim is to quantify and rank each protein’s simultaneous impact into multiple complexes based on network topology and clustering. Package also enables estimating of co-occurrence of diseases across the network and specific clusters pointing towards shared/common mechanisms.

Maintained by Anatoly Sorokin. Last updated 19 days ago.

software graphandnetwork network

4.0 match 3 stars 5.90 score 35 scripts

reumandc

wsyn:Wavelet Approaches to Studies of Synchrony in Ecology and Other Fields

Tools for a wavelet-based approach to analyzing spatial synchrony, principally in ecological data. Some tools will be useful for studying community synchrony. See, for instance, Sheppard et al (2016) <doi: 10.1038/NCLIMATE2991>, Sheppard et al (2017) <doi: 10.1051/epjnbp/2017000>, Sheppard et al (2019) <doi: 10.1371/journal.pcbi.1006744>.

Maintained by Daniel C. Reuman. Last updated 3 years ago.

4.9 match 1 stars 4.80 score 125 scripts

brockk

escalation:A Modular Approach to Dose-Finding Clinical Trials

Methods for working with dose-finding clinical trials. We provide implementations of many dose-finding clinical trial designs, including the continual reassessment method (CRM) by O'Quigley et al. (1990) <doi:10.2307/2531628>, the toxicity probability interval (TPI) design by Ji et al. (2007) <doi:10.1177/1740774507079442>, the modified TPI (mTPI) design by Ji et al. (2010) <doi:10.1177/1740774510382799>, the Bayesian optimal interval design (BOIN) by Liu & Yuan (2015) <doi:10.1111/rssc.12089>, EffTox by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; the design of Wages & Tait (2015) <doi:10.1080/10543406.2014.920873>, and the 3+3 described by Korn et al. (1994) <doi:10.1002/sim.4780131802>. All designs are implemented with a common interface. We also offer optional additional classes to tailor the behaviour of all designs, including avoiding skipping doses, stopping after n patients have been treated at the recommended dose, stopping when a toxicity condition is met, or demanding that n patients are treated before stopping is allowed. By daisy-chaining together these classes using the pipe operator from 'magrittr', it is simple to tailor the behaviour of a dose-finding design so it behaves how the trialist wants. Having provided a flexible interface for specifying designs, we then provide functions to run simulations and calculate dose-paths for future cohorts of patients.

Maintained by Kristian Brock. Last updated 2 months ago.

2.9 match 15 stars 7.91 score 67 scripts

avi-kenny

SimEngine:A Modular Framework for Statistical Simulations in R

An open-source R package for structuring, maintaining, running, and debugging statistical simulations on both local and cluster-based computing environments.See full documentation at <https://avi-kenny.github.io/SimEngine/>.

Maintained by Avi Kenny. Last updated 23 days ago.

3.0 match 12 stars 7.18 score 50 scripts

biorgeo

bioregion:Comparison of Bioregionalisation Methods

The main purpose of this package is to propose a transparent methodological framework to compare bioregionalisation methods based on hierarchical and non-hierarchical clustering algorithms (Kreft & Jetz (2010) <doi:10.1111/j.1365-2699.2010.02375.x>) and network algorithms (Lenormand et al. (2019) <doi:10.1002/ece3.4718> and Leroy et al. (2019) <doi:10.1111/jbi.13674>).

Maintained by Maxime Lenormand. Last updated 11 days ago.

biogeography bioregion bioregionalization cpp

3.4 match 7 stars 6.27 score 11 scripts

r-world-devs

shinyCohortBuilder:Modular Cohort-Building Framework for Analytical Dashboards

You can easily add advanced cohort-building component to your analytical dashboard or simple 'Shiny' app. Then you can instantly start building cohorts using multiple filters of different types, filtering datasets, and filtering steps. Filters can be complex and data-specific, and together with multiple filtering steps you can use complex filtering rules. The cohort-building sidebar panel allows you to easily work with filters, add and remove filtering steps. It helps you with handling missing values during filtering, and provides instant filtering feedback with filter feedback plots. The GUI panel is not only compatible with native shiny bookmarking, but also provides reproducible R code.

Maintained by Krystian Igras. Last updated 1 months ago.

2.9 match 7 stars 7.05 score 40 scripts

petervdberg

requireR:R Source Code Modularizer

Modularizes source code. Keeps the global environment clean, explicifies interdependencies. Inspired by 'RequireJS'<http://requirejs.org/>.

Maintained by Peter van den Berg. Last updated 8 years ago.

5.4 match 3.70 score 2 scripts

langejens

CliquePercolation:Clique Percolation for Networks

Clique percolation community detection for weighted and unweighted networks as well as threshold and plotting functions. For more information see Farkas et al. (2007) <doi:10.1088/1367-2630/9/6/180> and Palla et al. (2005) <doi:10.1038/nature03607>.

Maintained by Jens Lange. Last updated 1 years ago.

3.5 match 4 stars 5.30 score 11 scripts 1 dependents

julienvollering

MIAmaxent:A Modular, Integrated Approach to Maximum Entropy Distribution Modeling

Tools for training, selecting, and evaluating maximum entropy (and standard logistic regression) distribution models. This package provides tools for user-controlled transformation of explanatory variables, selection of variables by nested model comparison, and flexible model evaluation and projection. It follows principles based on the maximum- likelihood interpretation of maximum entropy modeling, and uses infinitely- weighted logistic regression for model fitting. The package is described in Vollering et al. (2019; <doi:10.1002/ece3.5654>).

Maintained by Julien Vollering. Last updated 7 months ago.

2.9 match 14 stars 6.53 score 30 scripts

robinhankin

elliptic:Weierstrass and Jacobi Elliptic Functions

A suite of elliptic and related functions including Weierstrass and Jacobi forms. Also includes various tools for manipulating and visualizing complex functions.

Maintained by Robin K. S. Hankin. Last updated 12 days ago.

2.0 match 3 stars 9.31 score 54 scripts 79 dependents

canmod

macpan2:Fast and Flexible Compartmental Modelling

Fast and flexible compartmental modelling with Template Model Builder.

Maintained by Steve Walker. Last updated 2 days ago.

compartmental-models epidemiology forecasting mixed-effects model-fitting optimization simulation simulation-modeling cpp

2.0 match 4 stars 8.89 score 246 scripts 1 dependents

rstudio

vetiver:Version, Share, Deploy, and Monitor Models

The goal of 'vetiver' is to provide fluent tooling to version, share, deploy, and monitor a trained model. Functions handle both recording and checking the model's input data prototype, and predicting from a remote API endpoint. The 'vetiver' package is extensible, with generics that can support many kinds of models.

Maintained by Julia Silge. Last updated 5 months ago.

1.7 match 185 stars 10.48 score 466 scripts 1 dependents

mikemahoney218

heddlr:Dynamic R Markdown Document Generation

Helper functions designed to make dynamically generating R Markdown documents easier by providing a simple and tidy way to create report pieces, shape them to your data, and combine them for exporting into a single R Markdown document.

Maintained by Michael Mahoney. Last updated 4 years ago.

heddlr rmarkdown

3.3 match 27 stars 5.13 score 10 scripts

aljensen89

CommKern:Network-Based Communities and Kernel Machine Methods

Analysis of network community objects with applications to neuroimaging data. There are two main components to this package. The first is the hierarchical multimodal spinglass (HMS) algorithm, which is a novel community detection algorithm specifically tailored to the unique issues within brain connectivity. The other is a suite of semiparametric kernel machine methods that allow for statistical inference to be performed to test for potential associations between these community structures and an outcome of interest (binary or continuous).

Maintained by Alexandria Jensen. Last updated 2 years ago.

3.9 match 4.11 score 26 scripts

ezetoum

HBV.IANIGLA:Modular Hydrological Model

The HBV hydrological model (Bergström, S. and Lindström, G., (2015) <doi:10.1002/hyp.10510>) has been split in modules to allow the user to build his/her own model. This version was developed by the author in IANIGLA-CONICET (Instituto Argentino de Nivologia, Glaciologia y Ciencias Ambientales - Consejo Nacional de Investigaciones Cientificas y Tecnicas) for hydroclimatic studies in the Andes. HBV.IANIGLA incorporates routines for clean and debris covered glacier melt simulations.

Maintained by Ezequiel Toum. Last updated 2 years ago.

cpp

3.3 match 4.56 score 12 scripts

alextkalinka

linkcomm:Tools for Generating, Visualizing, and Analysing Link Communities in Networks

Link communities reveal the nested and overlapping structure in networks, and uncover the key nodes that form connections to multiple communities. linkcomm provides a set of tools for generating, visualizing, and analysing link communities in networks of arbitrary size and type. The linkcomm package also includes tools for generating, visualizing, and analysing Overlapping Cluster Generator (OCG) communities. Kalinka and Tomancak (2011) <doi:10.1093/bioinformatics/btr311>.

Maintained by Alex T. Kalinka. Last updated 4 years ago.

clustering networks networks-biology visualization cpp

1.9 match 7 stars 7.53 score 115 scripts 4 dependents

bioc

edge:Extraction of Differential Gene Expression

The edge package implements methods for carrying out differential expression analyses of genome-wide gene expression studies. Significance testing using the optimal discovery procedure and generalized likelihood ratio tests (equivalent to F-tests and t-tests) are implemented for general study designs. Special functions are available to facilitate the analysis of common study designs, including time course experiments. Other packages such as sva and qvalue are integrated in edge to provide a wide range of tools for gene expression analysis.

Maintained by John D. Storey. Last updated 5 months ago.

multiplecomparison differentialexpression timecourse regression geneexpression dataimport

1.8 match 21 stars 7.77 score 62 scripts

bioc

crisprDesign:Comprehensive design of CRISPR gRNAs for nucleases and base editors

Provides a comprehensive suite of functions to design and annotate CRISPR guide RNA (gRNAs) sequences. This includes on- and off-target search, on-target efficiency scoring, off-target scoring, full gene and TSS contextual annotations, and SNP annotation (human only). It currently support five types of CRISPR modalities (modes of perturbations): CRISPR knockout, CRISPR activation, CRISPR inhibition, CRISPR base editing, and CRISPR knockdown. All types of CRISPR nucleases are supported, including DNA- and RNA-target nucleases such as Cas9, Cas12a, and Cas13d. All types of base editors are also supported. gRNA design can be performed on reference genomes, transcriptomes, and custom DNA and RNA sequences. Both unpaired and paired gRNA designs are enabled.

Maintained by Jean-Philippe Fortin. Last updated 11 days ago.

crispr functionalgenomics genetarget bioconductor bioconductor-package crispr-cas9 crispr-design crispr-target genomics-analysis grna grna-sequence grna-sequences sgrna sgrna-design

1.7 match 22 stars 8.28 score 80 scripts 3 dependents

cmclean5

rSpectral:Spectral Modularity Clustering

Implements the network clustering algorithm described in Newman (2006) <doi:10.1103/PhysRevE.74.036104>. The complete iterative algorithm comprises of two steps. In the first step, the network is expressed in terms of its leading eigenvalue and eigenvector and recursively partition into two communities. Partitioning occurs if the maximum positive eigenvalue is greater than the tolerance (10e-5) for the current partition, and if it results in a positive contribution to the Modularity. Given an initial separation using the leading eigen step, 'rSpectral' then continues to maximise for the change in Modularity using a fine-tuning step - or variate thereof. The first stage here is to find the node which, when moved from one community to another, gives the maximum change in Modularity. This node’s community is then fixed and we repeat the process until all nodes have been moved. The whole process is repeated from this new state until the change in the Modularity, between the new and old state, is less than the predefined tolerance. A slight variant of the fine-tuning step, which can improve speed of the calculation, is also provided. Instead of moving each node into each community in turn, we only consider moves of neighbouring nodes, found in different communities, to the community of the current node of interest. The two steps process is repeatedly applied to each new community found, subdivided each community into two new communities, until we are unable to find any division that results in a positive change in Modularity.

Maintained by Anatoly Sorokin. Last updated 2 years ago.

openblas cpp

4.3 match 1 stars 3.18 score 9 scripts 1 dependents

alexchristensen

SemNeT:Methods and Measures for Semantic Network Analysis

Implements several functions for the analysis of semantic networks including different network estimation algorithms, partial node bootstrapping (Kenett, Anaki, & Faust, 2014 <doi:10.3389/fnhum.2014.00407>), random walk simulation (Kenett & Austerweil, 2016 <http://alab.psych.wisc.edu/papers/files/Kenett16CreativityRW.pdf>), and a function to compute global network measures. Significance tests and plotting features are also implemented.

Maintained by Alexander P. Christensen. Last updated 2 years ago.

semantic-network-analysis

3.0 match 23 stars 4.51 score 28 scripts

wzhang40

BipartiteModularityMaximization:Partition Bipartite Network into Non-Overlapping Biclusters by Optimizing Bipartite Modularity

Function bipmod() that partitions a bipartite network into non-overlapping biclusters by maximizing bipartite modularity defined in Barber (2007) <doi:10.1103/PhysRevE.76.066102> using the bipartite version of the algorithm described in Treviño (2015) <doi:10.1088/1742-5468/2015/02/P02003>.

Maintained by Weibin Zhang. Last updated 2 years ago.

cpp

5.0 match 2.70 score 6 scripts

fcampelo

ExpDE:Modular Differential Evolution for Experimenting with Operators

Modular implementation of the Differential Evolution algorithm for experimenting with different types of operators.

Maintained by Felipe Campelo. Last updated 6 years ago.

3.6 match 2 stars 3.70 score 25 scripts

bioc

BloodGen3Module:This R package for performing module repertoire analyses and generating fingerprint representations

The BloodGen3Module package provides functions for R user performing module repertoire analyses and generating fingerprint representations. Functions can perform group comparison or individual sample analysis and visualization by fingerprint grid plot or fingerprint heatmap. Module repertoire analyses typically involve determining the percentage of the constitutive genes for each module that are significantly increased or decreased. As we describe in details;https://www.biorxiv.org/content/10.1101/525709v2 and https://pubmed.ncbi.nlm.nih.gov/33624743/, the results of module repertoire analyses can be represented in a fingerprint format, where red and blue spots indicate increases or decreases in module activity. These spots are subsequently represented either on a grid, with each position being assigned to a given module, or in a heatmap where the samples are arranged in columns and the modules in rows.

Maintained by Darawan Rinchai. Last updated 5 months ago.

software visualization geneexpression

3.0 match 4.30 score 5 scripts

bioc

ALDEx2:Analysis Of Differential Abundance Taking Sample and Scale Variation Into Account

A differential abundance analysis for the comparison of two or more conditions. Useful for analyzing data from standard RNA-seq or meta-RNA-seq assays as well as selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, optimized for three or more experimental replicates. The method infers biological and sampling variation to calculate the expected false discovery rate, given the variation, based on a Wilcoxon Rank Sum test and Welch's t-test (via aldex.ttest), a Kruskal-Wallis test (via aldex.kw), a generalized linear model (via aldex.glm), or a correlation test (via aldex.corr). All tests report predicted p-values and posterior Benjamini-Hochberg corrected p-values. ALDEx2 also calculates expected standardized effect sizes for paired or unpaired study designs. ALDEx2 can now be used to estimate the effect of scale on the results and report on the scale-dependent robustness of results.

Maintained by Greg Gloor. Last updated 5 months ago.

differentialexpression rnaseq transcriptomics geneexpression dnaseq chipseq bayesian sequencing software microbiome metagenomics immunooncology scale simulation posterior p-value

1.2 match 28 stars 10.70 score 424 scripts 3 dependents

openanalytics

clinDataReview:Clinical Data Review Tool

Creation of interactive tables, listings and figures ('TLFs') and associated report for exploratory analysis of data in a clinical trial, e.g. for clinical oversight activities. Interactive figures include sunburst, treemap, scatterplot, line plot and barplot of counts data. Interactive tables include table of summary statistics (as counts of adverse events, enrollment table) and listings. Possibility to compare data (summary table or listing) across two data batches/sets. A clinical data review report is created via study-specific configuration files and template 'R Markdown' reports contained in the package.

Maintained by Laure Cougnaud. Last updated 9 months ago.

1.5 match 11 stars 7.10 score 36 scripts

tom-wolff

ideanet:Integrating Data Exchange and Analysis for Networks ('ideanet')

A suite of convenient tools for social network analysis geared toward students, entry-level users, and non-expert practitioners. ‘ideanet’ features unique functions for the processing and measurement of sociocentric and egocentric network data. These functions automatically generate node- and system-level measures commonly used in the analysis of these types of networks. Outputs from these functions maximize the ability of novice users to employ network measurements in further analyses while making all users less prone to common data analytic errors. Additionally, ‘ideanet’ features an R Shiny graphic user interface that allows novices to explore network data with minimal need for coding.

Maintained by Tom Wolff. Last updated 3 days ago.

1.5 match 6 stars 6.80 score 10 scripts

stla

jacobi:Jacobi Theta Functions and Related Functions

Evaluation of the Jacobi theta functions and related functions: Weierstrass elliptic function, Weierstrass sigma function, Weierstrass zeta function, Klein j-function, Dedekind eta function, lambda modular function, Jacobi elliptic functions, Neville theta functions, Eisenstein series, lemniscate elliptic functions, elliptic alpha function, Rogers-Ramanujan continued fractions, and Dixon elliptic functions. Complex values of the variable are supported.

Maintained by Stéphane Laurent. Last updated 1 years ago.

elliptic-functions theta-functions cpp

2.5 match 2 stars 4.01 score 103 scripts

thinkr-open

rusk:Beautiful Graphical Representation of Multiplication Tables on a Modular Circle

By placing on a circle 10 points numbered from 1 to 10, and connecting them by a straight line to the point corresponding to its multiplication by 2. (1 must be connected to 1 * 2 = 2, point 2 must be set to 2 * 2 = 4, point 3 to 3 * 2 = 6 and so on). You will obtain an amazing geometric figure that complicates and beautifies itself by varying the number of points and the multiplication table you use.

Maintained by Vincent Guyader. Last updated 6 years ago.

thinkr-not-maintained

2.9 match 6 stars 3.48 score 9 scripts

bioc

miRSM:Inferring miRNA sponge modules in heterogeneous data

The package aims to identify miRNA sponge or ceRNA modules in heterogeneous data. It provides several functions to study miRNA sponge modules at single-sample and multi-sample levels, including popular methods for inferring gene modules (candidate miRNA sponge or ceRNA modules), and two functions to identify miRNA sponge modules at single-sample and multi-sample levels, as well as several functions to conduct modular analysis of miRNA sponge modules.

Maintained by Junpeng Zhang. Last updated 5 months ago.

geneexpression biomedicalinformatics clustering genesetenrichment microarray software generegulation genetarget cerna mirna mirna-sponge mirna-targets modules openjdk

1.7 match 4 stars 5.68 score 5 scripts

simon-smart88

shinyscholar:A Template for Creating Reproducible 'shiny' Applications

Create a skeleton 'shiny' application with create_template() that is reproducible, can be saved and meets academic standards for attribution. Forked from 'wallace'. Code is split into modules that are loaded and linked together automatically and each call one function. Guidance pages explain modules to users and flexible logging informs them of any errors. Options enable asynchronous operations, viewing of source code, interactive maps and data tables. Use to create complex analytical applications, following best practices in open science and software development. Includes functions for automating repetitive development tasks and an example application at run_shinyscholar() that requires install.packages("shinyscholar", dependencies = TRUE). A guide to developing applications can be found on the package website.

Maintained by Simon E. H. Smart. Last updated 1 months ago.

1.8 match 20 stars 5.36 score 5 scripts

cran

modMax:Community Structure Detection via Modularity Maximization

The algorithms implemented here are used to detect the community structure of a network. These algorithms follow different approaches, but are all based on the concept of modularity maximization.

Maintained by Maria Schelling. Last updated 10 years ago.

7.1 match 2 stars 1.30 score 10 scripts

bioc

GenomicDistributions:GenomicDistributions: fast analysis of genomic intervals with Bioconductor

If you have a set of genomic ranges, this package can help you with visualization and comparison. It produces several kinds of plots, for example: Chromosome distribution plots, which visualize how your regions are distributed over chromosomes; feature distance distribution plots, which visualizes how your regions are distributed relative to a feature of interest, like Transcription Start Sites (TSSs); genomic partition plots, which visualize how your regions overlap given genomic features such as promoters, introns, exons, or intergenic regions. It also makes it easy to compare one set of ranges to another.

Maintained by Kristyna Kupkova. Last updated 5 months ago.

software genomeannotation genomeassembly datarepresentation sequencing coverage functionalgenomics visualization

1.2 match 26 stars 7.44 score 25 scripts

psavary3

graph4lg:Build Graphs for Landscape Genetics Analysis

Build graphs for landscape genetics analysis. This set of functions can be used to import and convert spatial and genetic data initially in different formats, import landscape graphs created with 'GRAPHAB' software (Foltete et al., 2012) <doi:10.1016/j.envsoft.2012.07.002>, make diagnosis plots of isolation by distance relationships in order to choose how to build genetic graphs, create graphs with a large range of pruning methods, weight their links with several genetic distances, plot and analyse graphs, compare them with other graphs. It uses functions from other packages such as 'adegenet' (Jombart, 2008) <doi:10.1093/bioinformatics/btn129> and 'igraph' (Csardi et Nepusz, 2006) <https://igraph.org/>. It also implements methods commonly used in landscape genetics to create graphs, described by Dyer et Nason (2004) <doi:10.1111/j.1365-294X.2004.02177.x> and Greenbaum et Fefferman (2017) <doi:10.1111/mec.14059>, and to analyse distance data (van Strien et al., 2015) <doi:10.1038/hdy.2014.62>.

Maintained by Paul Savary. Last updated 2 years ago.

1.8 match 3 stars 4.51 score 54 scripts

kgates

perturbR:Random Perturbation of Count Matrices

The perturbR() function incrementally perturbs network edges (using the rewireR function)and compares the resulting community detection solutions from the rewired networks with the solution found for the original network. These comparisons aid in understanding the stability of the original solution. The package requires symmetric, weighted (specifically, count) matrices/networks.

Maintained by KM Gates. Last updated 6 years ago.

2.4 match 3.26 score 12 scripts 1 dependents

bioc

GenomAutomorphism:Compute the automorphisms between DNA's Abelian group representations

This is a R package to compute the automorphisms between pairwise aligned DNA sequences represented as elements from a Genomic Abelian group. In a general scenario, from genomic regions till the whole genomes from a given population (from any species or close related species) can be algebraically represented as a direct sum of cyclic groups or more specifically Abelian p-groups. Basically, we propose the representation of multiple sequence alignments of length N bp as element of a finite Abelian group created by the direct sum of homocyclic Abelian group of prime-power order.

Maintained by Robersy Sanchez. Last updated 3 months ago.

mathematicalbiology comparativegenomics functionalgenomics multiplesequencealignment wholegenome genetic-code genetic-code-algebra genome genome-algebra

1.8 match 4.30 score 9 scripts

tpook92

MoBPS:Modular Breeding Program Simulator

Framework for the simulation framework for the simulation of complex breeding programs and compare their economic and genetic impact. The package is also used as the background simulator for our a web-based interface <http:www.mobps.de>. Associated publication: Pook et al. (2020) <doi:10.1534/g3.120.401193>.

Maintained by Torsten Pook. Last updated 3 years ago.

3.1 match 2.35 score 45 scripts

bioc

parody:Parametric And Resistant Outlier DYtection

Provide routines for univariate and multivariate outlier detection with a focus on parametric methods, but support for some methods based on resistant statistics.

Maintained by Vince Carey. Last updated 1 months ago.

multiplecomparison

1.8 match 4.08 score 12 scripts

bioc

MODA:MODA: MOdule Differential Analysis for weighted gene co-expression network

MODA can be used to estimate and construct condition-specific gene co-expression networks, and identify differentially expressed subnetworks as conserved or condition specific modules which are potentially associated with relevant biological processes.

Maintained by Dong Li. Last updated 5 months ago.

geneexpression microarray differentialexpression network

2.0 match 3.30 score 9 scripts

mortamini

CMAPSS:Commercial Modular Aero-Propulsion System Simulation Data Set

Contains the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) data set.

Maintained by Morteza Amini. Last updated 4 years ago.

3.4 match 1.95 score 1 dependents

pik-piam

goxygen:In-Code Documentation for 'GAMS'

A collection of tools which extract a model documentation from 'GAMS' code and comments. In order to use the package you need to install 'pandoc' and 'pandoc-citeproc' first (<https://pandoc.org/>).

Maintained by Jan Philipp Dietrich. Last updated 1 years ago.

1.2 match 6 stars 5.43 score 4 scripts

s-u

Cairo:R Graphics Device using Cairo Graphics Library for Creating High-Quality Bitmap (PNG, JPEG, TIFF), Vector (PDF, SVG, PostScript) and Display (X11 and Win32) Output

R graphics device using cairographics library that can be used to create high-quality vector (PDF, PostScript and SVG) and bitmap output (PNG,JPEG,TIFF), and high-quality rendering in displays (X11 and Win32). Since it uses the same back-end for all output, copying across formats is WYSIWYG. Files are created without the dependence on X11 or other external programs. This device supports alpha channel (semi-transparent drawing) and resulting images can contain transparent and semi-transparent regions. It is ideal for use in server environments (file output) and as a replacement for other devices that don't have Cairo's capabilities such as alpha support or anti-aliasing. Backends are modular such that any subset of backends is supported.

Maintained by Simon Urbanek. Last updated 7 months ago.

freetype cairo libx11 libjpeg-turbo harfbuzz icu tiff

0.5 match 14 stars 12.52 score 3.9k scripts 71 dependents

joycekang

symphony:Efficient and Precise Single-Cell Reference Atlas Mapping

Implements the Symphony single-cell reference building and query mapping algorithms and additional functions described in Kang et al <https://www.nature.com/articles/s41467-021-25957-x>.

Maintained by Joyce Kang. Last updated 2 years ago.

openblas cpp

1.6 match 3.83 score 134 scripts

cran

Diderot:Bibliographic Network Analysis

Enables the user to build a citation network/graph from bibliographic data and, based on modularity and heterocitation metrics, assess the degree of awareness/cross-fertilization between two corpora/communities. This toolset is optimized for Scopus data.

Maintained by Christian Vincenot. Last updated 5 years ago.

5.7 match 1.00 score

pharmaverse

ggsurvfit:Flexible Time-to-Event Figures

Ease the creation of time-to-event (i.e. survival) endpoint figures. The modular functions create figures ready for publication. Each of the functions that add to or modify the figure are written as proper 'ggplot2' geoms or stat methods, allowing the functions from this package to be combined with any function or customization from 'ggplot2' and other 'ggplot2' extension packages.

Maintained by Daniel D. Sjoberg. Last updated 2 months ago.

0.5 match 76 stars 10.50 score 640 scripts 2 dependents

predictiveecology

SpaDES.core:Core Utilities for Developing and Running Spatially Explicit Discrete Event Models

Provides the core framework for a discrete event system to implement a complete data-to-decisions, reproducible workflow. The core components facilitate the development of modular pieces, and enable the user to include additional functionality by running user-built modules. Includes conditional scheduling, restart after interruption, packaging of reusable modules, tools for developing arbitrary automated workflows, automated interweaving of modules of different temporal resolution, and tools for visualizing and understanding the within-project dependencies. The suggested package 'NLMR' can be installed from the repository (<https://PredictiveEcology.r-universe.dev>).

Maintained by Eliot J B McIntire. Last updated 19 days ago.

discrete-events-simulations simulation-framework simulation-modeling

0.5 match 10 stars 10.61 score 142 scripts 6 dependents

bioc

tidybulk:Brings transcriptomics to the tidyverse

This is a collection of utility functions that allow to perform exploration of and calculations to RNA sequencing data, in a modular, pipe-friendly and tidy fashion.

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics bioconductor bulk-transcriptional-analyses deseq2 differential-expression edger ensembl-ids entrez gene-symbols gsea mds-dimensions pca pipe redundancy tibble tidy tidy-data tidyverse transcripts tsne

0.5 match 168 stars 9.48 score 172 scripts 1 dependents

yinxy1992

M2SMF:Multi-Modal Similarity Matrix Factorization for Integrative Multi-Omics Data Analysis

A new method to implement clustering from multiple modality data of certain samples, the function M2SMF() jointly factorizes multiple similarity matrices into a shared sub-matrix and several modality private sub-matrices, which is further used for clustering. Along with this method, we also provide function to calculate the similarity matrix and function to evaluate the best cluster number from the original data.

Maintained by Xiaoyao Yin. Last updated 5 years ago.

2.3 match 2.23 score 17 scripts

bavodc

actuaRE:Handling Hierarchically Structured Risk Factors using Random Effects Models

Using this package, you can fit a random effects model using either the hierarchical credibility model, a combination of the hierarchical credibility model with a generalized linear model or a Tweedie generalized linear mixed model. See Campo, B.D.C. and Antonio, K. (2023) <doi:10.1080/03461238.2022.2161413>.

Maintained by Campo Bavo D.C.. Last updated 2 years ago.

1.8 match 2.74 score 11 scripts

danielbr2

BLPestimatoR:Performs a BLP Demand Estimation

Provides the estimation algorithm to perform the demand estimation described in Berry, Levinsohn and Pakes (1995) <DOI:10.2307/2171802> . The routine uses analytic gradients and offers a large number of implemented integration methods and optimization routines.

Maintained by Daniel Brunner. Last updated 2 years ago.

openblas cpp

1.5 match 7 stars 3.21 score 23 scripts

ropensci

iheatmapr:Interactive, Complex Heatmaps

Make complex, interactive heatmaps. 'iheatmapr' includes a modular system for iteratively building up complex heatmaps, as well as the iheatmap() function for making relatively standard heatmaps.

Maintained by Alan OCallaghan. Last updated 7 months ago.

heatmap plotly interactive-visualizations data-visualization htmlwidgets peer-reviewed

0.5 match 267 stars 9.08 score 99 scripts 1 dependents

jleivacuadrado

VeryLargeIntegers:Store and Operate with Arbitrarily Large Integers

Multi-precision library that allows to store and operate with arbitrarily big integers without loss of precision. It includes a large list of tools to work with them, like: - Arithmetic and logic operators - Modular-arithmetic operators - Computer Number Theory utilities - Probabilistic primality tests - Factorization algorithms - Random generators of diferent types of integers.

Maintained by Javier Leiva Cuadrado. Last updated 2 years ago.

cpp

2.3 match 2.00 score 33 scripts 1 dependents

yinxy1992

M2SMJF:Multi-Modal Similarity Matrix Joint Factorization

A new method to implement clustering from multiple modality data of certain samples, the function M2SMjF() jointly factorizes multiple similarity matrices into a shared sub-matrix and several modality private sub-matrices, which is further used for clustering. Along with this method, we also provide function to calculate the similarity matrix and function to evaluate the best cluster number from the original data.

Maintained by Xiaoyao Yin. Last updated 4 years ago.

2.3 match 2.00 score 2 scripts

predictiveecology

SpaDES:Develop and Run Spatially Explicit Discrete Event Simulation Models

Metapackage for implementing a variety of event-based models, with a focus on spatially explicit models. These include raster-based, event-based, and agent-based models. The core simulation components (provided by 'SpaDES.core') are built upon a discrete event simulation (DES; see Matloff (2011) ch 7.8.3 <https://nostarch.com/artofr.htm>) framework that facilitates modularity, and easily enables the user to include additional functionality by running user-built simulation modules (see also 'SpaDES.tools'). Included are numerous tools to visualize rasters and other maps (via 'quickPlot'), and caching methods for reproducible simulations (via 'reproducible'). Tools for running simulation experiments are provided by 'SpaDES.experiment'. Additional functionality is provided by the 'SpaDES.addins' and 'SpaDES.shiny' packages.

Maintained by Alex M Chubaty. Last updated 4 months ago.

simulation-framework simulation-toolkit spatially-explicit-models

0.5 match 55 stars 8.87 score 227 scripts

tguillerme

dispRity:Measuring Disparity

A modular package for measuring disparity (multidimensional space occupancy). Disparity can be calculated from any matrix defining a multidimensional space. The package provides a set of implemented metrics to measure properties of the space and allows users to provide and test their own metrics. The package also provides functions for looking at disparity in a serial way (e.g. disparity through time) or per groups as well as visualising the results. Finally, this package provides several statistical tests for disparity analysis.

Maintained by Thomas Guillerme. Last updated 2 days ago.

disparity ecology multidimensionality palaeobiology

0.5 match 26 stars 8.69 score 220 scripts 1 dependents

nschuwirth

ecoval:Procedures for Ecological Assessment of Surface Waters

Functions for evaluating and visualizing ecological assessment procedures for surface waters containing physical, chemical and biological assessments in the form of value functions.

Maintained by Nele Schuwirth. Last updated 3 years ago.

3.2 match 1.34 score 22 scripts

jmanuelmk

CoNI:Correlation Guided Network Integration (CoNI)

Integrates two numerical omics data sets from the same samples using partial correlations. The output can be represented as a network, bipartite graph or a hypergraph structure. The method used in the package refers to Klaus et al (2021) <doi:10.1016/j.molmet.2021.101295>.

Maintained by José Manuel Monroy Kuhn. Last updated 3 years ago.

1.2 match 3.70 score 2 scripts

mlr-org

mlr3verse:Easily Install and Load the 'mlr3' Package Family

The 'mlr3' package family is a set of packages for machine-learning purposes built in a modular fashion. This wrapper package is aimed to simplify the installation and loading of the core 'mlr3' packages. Get more information about the 'mlr3' project at <https://mlr3book.mlr-org.com/>.

Maintained by Marc Becker. Last updated 2 months ago.

machine-learning meta mlr3

0.5 match 55 stars 8.32 score 720 scripts 1 dependents

bioc

nullranges:Generation of null ranges via bootstrapping or covariate matching

Modular package for generation of sets of ranges representing the null hypothesis. These can take the form of bootstrap samples of ranges (using the block bootstrap framework of Bickel et al 2010), or sets of control ranges that are matched across one or more covariates. nullranges is designed to be inter-operable with other packages for analysis of genomic overlap enrichment, including the plyranges Bioconductor package.

Maintained by Michael Love. Last updated 5 months ago.

visualization genesetenrichment functionalgenomics epigenetics generegulation genetarget genomeannotation annotation genomewideassociation histonemodification chipseq atacseq dnaseseq rnaseq hiddenmarkovmodel bioconductor bootstrap genomics matching statistics

0.5 match 27 stars 8.16 score 50 scripts 1 dependents

hesim-dev

hesim:Health Economic Simulation Modeling and Decision Analysis

A modular and computationally efficient R package for parameterizing, simulating, and analyzing health economic simulation models. The package supports cohort discrete time state transition models (Briggs et al. 1998) <doi:10.2165/00019053-199813040-00003>, N-state partitioned survival models (Glasziou et al. 1990) <doi:10.1002/sim.4780091106>, and individual-level continuous time state transition models (Siebert et al. 2012) <doi:10.1016/j.jval.2012.06.014>, encompassing both Markov (time-homogeneous and time-inhomogeneous) and semi-Markov processes. Decision uncertainty from a cost-effectiveness analysis is quantified with standard graphical and tabular summaries of a probabilistic sensitivity analysis (Claxton et al. 2005, Barton et al. 2008) <doi:10.1002/hec.985>, <doi:10.1111/j.1524-4733.2008.00358.x>. Use of C++ and data.table make individual-patient simulation, probabilistic sensitivity analysis, and incorporation of patient heterogeneity fast.

Maintained by Devin Incerti. Last updated 6 months ago.

health-economic-evaluation microsimulation simulation-modeling cpp

0.5 match 67 stars 8.12 score 41 scripts

openpharma

crmPack:Object-Oriented Implementation of CRM Designs

Implements a wide range of model-based dose escalation designs, ranging from classical and modern continual reassessment methods (CRMs) based on dose-limiting toxicity endpoints to dual-endpoint designs taking into account a biomarker/efficacy outcome. The focus is on Bayesian inference, making it very easy to setup a new design with its own JAGS code. However, it is also possible to implement 3+3 designs for comparison or models with non-Bayesian estimation. The whole package is written in a modular form in the S4 class system, making it very flexible for adaptation to new models, escalation or stopping rules. Further details are presented in Sabanes Bove et al. (2019) <doi:10.18637/jss.v089.i10>.

Maintained by Daniel Sabanes Bove. Last updated 2 months ago.

jags cpp

0.5 match 21 stars 7.79 score 208 scripts

bioc

MsFeatures:Functionality for Mass Spectrometry Features

The MsFeature package defines functionality for Mass Spectrometry features. This includes functions to group (LC-MS) features based on some of their properties, such as retention time (coeluting features), or correlation of signals across samples. This packge hence allows to group features, and its results can be used as an input for the `QFeatures` package which allows to aggregate abundance levels of features within each group. This package defines concepts and functions for base and common data types, implementations for more specific data types are expected to be implemented in the respective packages (such as e.g. `xcms`). All functionality of this package is implemented in a modular way which allows combination of different grouping approaches and enables its re-use in other R packages.

Maintained by Johannes Rainer. Last updated 5 months ago.

infrastructure massspectrometry metabolomics

0.5 match 7 stars 7.70 score 32 scripts 12 dependents

project-gen3sis

gen3sis:General Engine for Eco-Evolutionary Simulations

Contains an engine for spatially-explicit eco-evolutionary mechanistic models with a modular implementation and several support functions. It allows exploring the consequences of ecological and macroevolutionary processes across realistic or theoretical spatio-temporal landscapes on biodiversity patterns as a general term. Reference: Oskar Hagen, Benjamin Flueck, Fabian Fopp, Juliano S. Cabral, Florian Hartig, Mikael Pontarp, Thiago F. Rangel, Loic Pellissier (2021) "gen3sis: A general engine for eco-evolutionary simulations of the processes that shape Earth's biodiversity" <doi:10.1371/journal.pbio.3001340>.

Maintained by Oskar Hagen. Last updated 1 years ago.

biodiversity ecology evolution mechanistic model modeling simulation cpp

0.5 match 29 stars 7.56 score 69 scripts

cardiomoon

editData:'RStudio' Addin for Editing a 'data.frame'

An 'RStudio' addin for editing a 'data.frame' or a 'tibble'. You can delete, add or update a 'data.frame' without coding. You can get resultant data as a 'data.frame'. In the package, modularized 'shiny' app codes are provided. These modules are intended for reuse across applications.

Maintained by Keon-Woong Moon. Last updated 4 years ago.

0.5 match 33 stars 7.34 score 63 scripts 4 dependents

bioc

cola:A Framework for Consensus Partitioning

Subgroup classification is a basic task in genomic data analysis, especially for gene expression and DNA methylation data analysis. It can also be used to test the agreement to known clinical annotations, or to test whether there exist significant batch effects. The cola package provides a general framework for subgroup classification by consensus partitioning. It has the following features: 1. It modularizes the consensus partitioning processes that various methods can be easily integrated. 2. It provides rich visualizations for interpreting the results. 3. It allows running multiple methods at the same time and provides functionalities to straightforward compare results. 4. It provides a new method to extract features which are more efficient to separate subgroups. 5. It automatically generates detailed reports for the complete analysis. 6. It allows applying consensus partitioning in a hierarchical manner.

Maintained by Zuguang Gu. Last updated 1 months ago.

clustering geneexpression classification software consensus-clustering cpp

0.5 match 61 stars 7.49 score 112 scripts

alexander-pastukhov

saccadr:Extract Saccades via an Ensemble of Methods Approach

A modular and extendable approach to extract (micro)saccades from gaze samples via an ensemble of methods. Although there is an agreement about a general definition of a saccade, the more specific details are harder to agree upon. Therefore, there are numerous algorithms that extract saccades based on various heuristics, which differ in the assumptions about velocity, acceleration, etc. The package uses three methods (Engbert and Kliegl (2003) <doi:10.1016/S0042-6989(03)00084-1>, Otero-Millan et al. (2014)<doi:10.1167/14.2.18>, and Nyström and Holmqvist (2010) <doi:10.3758/BRM.42.1.188>) to label individual samples and then applies a majority vote approach to identify saccades. The package includes three methods but can be extended via custom functions. It also uses a modular approach to compute velocity and acceleration from noisy samples. Finally, you can obtain methods votes per gaze sample instead of saccades.

Maintained by Alexander Pastukhov. Last updated 2 years ago.

cpp

0.8 match 4 stars 4.90 score 8 scripts

funecology

fundiversity:Easy Computation of Functional Diversity Indices

Computes six functional diversity indices. These are namely, Functional Divergence (FDiv), Function Evenness (FEve), Functional Richness (FRic), Functional Richness intersections (FRic_intersect), Functional Dispersion (FDis), and Rao's entropy (Q) (reviewed in Villéger et al. 2008 <doi:10.1890/07-1206.1>). Provides efficient, modular, and parallel functions to compute functional diversity indices (Grenié & Gruson 2023 <doi:10.1111/ecog.06585>).

Maintained by Matthias Grenié. Last updated 8 months ago.

biodiversity biodiversity-indicators biodiversity-informatics functional-diversity functional-ecology functional-trait functional-traits trait trait-based traits

0.5 match 38 stars 7.34 score 38 scripts

bioc

BUSpaRse:kallisto | bustools R utilities

The kallisto | bustools pipeline is a fast and modular set of tools to convert single cell RNA-seq reads in fastq files into gene count or transcript compatibility counts (TCC) matrices for downstream analysis. Central to this pipeline is the barcode, UMI, and set (BUS) file format. This package serves the following purposes: First, this package allows users to manipulate BUS format files as data frames in R and then convert them into gene count or TCC matrices. Furthermore, since R and Rcpp code is easier to handle than pure C++ code, users are encouraged to tweak the source code of this package to experiment with new uses of BUS format and different ways to convert the BUS file into gene count matrix. Second, this package can conveniently generate files required to generate gene count matrices for spliced and unspliced transcripts for RNA velocity. Here biotypes can be filtered and scaffolds and haplotypes can be removed, and the filtered transcriptome can be extracted and written to disk. Third, this package implements utility functions to get transcripts and associated genes required to convert BUS files to gene count matrices, to write the transcript to gene information in the format required by bustools, and to read output of bustools into R as sparses matrices.

Maintained by Lambda Moses. Last updated 5 months ago.

singlecell rnaseq workflowstep cpp

0.5 match 9 stars 7.35 score 165 scripts

dandls

counterfactuals:Counterfactual Explanations

Modular and unified R6-based interface for counterfactual explanation methods. The following methods are currently implemented: Burghmans et al. (2022) <doi:10.48550/arXiv.2104.07411>, Dandl et al. (2020) <doi:10.1007/978-3-030-58112-1_31> and Wexler et al. (2019) <doi:10.1109/TVCG.2019.2934619>. Optional extensions allow these methods to be applied to a variety of models and use cases. Once generated, the counterfactuals can be analyzed and visualized by provided functionalities.

Maintained by Susanne Dandl. Last updated 5 months ago.

interpretable-machine-learning local-explanations model-agnostic-explanations

0.5 match 21 stars 7.14 score 22 scripts

tguillerme

treats:Trees and Traits Simulations

A modular package for simulating phylogenetic trees and species traits jointly. Trees can be simulated using modular birth-death parameters (e.g. changing starting parameters or algorithm rules). Traits can be simulated in any way designed by the user. The growth of the tree and the traits can influence each other through modifiers objects providing rules for affecting each other. Finally, events can be created to modify both the tree and the traits under specific conditions ( Guillerme, 2024 <DOI:10.1111/2041-210X.14306>).

Maintained by Thomas Guillerme. Last updated 2 months ago.

0.8 match 3 stars 4.63 score 19 scripts

bioc

systemPipeShiny:systemPipeShiny: An Interactive Framework for Workflow Management and Visualization

systemPipeShiny (SPS) extends the widely used systemPipeR (SPR) workflow environment with a versatile graphical user interface provided by a Shiny App. This allows non-R users, such as experimentalists, to run many systemPipeR’s workflow designs, control, and visualization functionalities interactively without requiring knowledge of R. Most importantly, SPS has been designed as a general purpose framework for interacting with other R packages in an intuitive manner. Like most Shiny Apps, SPS can be used on both local computers as well as centralized server-based deployments that can be accessed remotely as a public web service for using SPR’s functionalities with community and/or private data. The framework can integrate many core packages from the R/Bioconductor ecosystem. Examples of SPS’ current functionalities include: (a) interactive creation of experimental designs and metadata using an easy to use tabular editor or file uploader; (b) visualization of workflow topologies combined with auto-generation of R Markdown preview for interactively designed workflows; (d) access to a wide range of data processing routines; (e) and an extendable set of visualization functionalities. Complex visual results can be managed on a 'Canvas Workbench’ allowing users to organize and to compare plots in an efficient manner combined with a session snapshot feature to continue work at a later time. The present suite of pre-configured visualization examples. The modular design of SPR makes it easy to design custom functions without any knowledge of Shiny, as well as extending the environment in the future with contributions from the community.

Maintained by Le Zhang. Last updated 5 months ago.

shinyapps infrastructure dataimport sequencing qualitycontrol reportwriting experimentaldesign clustering bioconductor bioconductor-package data-visualization shiny systempiper

0.5 match 33 stars 7.03 score 36 scripts

trenchproject

TrenchR:Tools for Microclimate and Biophysical Ecology

Tools for translating environmental change into organismal response. Microclimate models to vertically scale weather station data to organismal heights. The biophysical modeling tools include both general models for heat flows and specific models to predict body temperatures for a variety of ectothermic taxa. Additional functions model and temporally partition air and soil temperatures and solar radiation. Utility functions estimate the organismal and environmental parameters needed for biophysical ecology. 'TrenchR' focuses on relatively simple and modular functions so users can create transparent and flexible biophysical models. Many functions are derived from Gates (1980) <doi:10.1007/978-1-4612-6024-0> and Campbell and Norman (1988) <isbn:9780387949376>.

Maintained by Lauren Buckley. Last updated 1 years ago.

0.5 match 13 stars 6.89 score 43 scripts

uscbiostats

fmcmc:A friendly MCMC framework

Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC) framework for implementing Metropolis-Hastings algorithm in a modular way allowing users to specify automatic convergence checker, personalized transition kernels, and out-of-the-box multiple MCMC chains using parallel computing. Most of the methods implemented in this package can be found in Brooks et al. (2011, ISBN 9781420079425). Among the methods included, we have: Haario (2001) <doi:10.1007/s11222-011-9269-5> Adaptive Metropolis, Vihola (2012) <doi:10.1007/s11222-011-9269-5> Robust Adaptive Metropolis, and Thawornwattana et al. (2018) <doi:10.1214/17-BA1084> Mirror transition kernels.

Maintained by George Vega Yon. Last updated 1 years ago.

adaptive bayesian-inference markov-chain-monte-carlo mcmc metropolis-hastings parallel-computing

0.5 match 16 stars 6.79 score 86 scripts 1 dependents

cardiomoon

rrtable:Reproducible Research with a Table of R Codes

Makes documents containing plots and tables from a table of R codes. Can make "HTML", "pdf('LaTex')", "docx('MS Word')" and "pptx('MS Powerpoint')" documents with or without R code. In the package, modularized 'shiny' app codes are provided. These modules are intended for reuse across applications.

Maintained by Keon-Woong Moon. Last updated 2 years ago.

0.5 match 3 stars 6.45 score 76 scripts 2 dependents

rpahl

pipeflow:Lightweight, General-Purpose Data Analysis Pipelines

A lightweight yet powerful framework for building robust data analysis pipelines. With 'pipeflow', you initialize a pipeline with your dataset and construct workflows step by step by adding R functions. You can modify, remove, or insert steps and parameters at any stage, while 'pipeflow' ensures the pipeline's integrity. Overall, this package offers a beginner-friendly framework that simplifies and streamlines the development of data analysis pipelines by making them modular, intuitive, and adaptable.

Maintained by Roman Pahl. Last updated 2 months ago.

pipeline-tools reproducible-research

0.5 match 13 stars 6.35 score 19 scripts

fcampelo

MOEADr:Component-Wise MOEA/D Implementation

Modular implementation of Multiobjective Evolutionary Algorithms based on Decomposition (MOEA/D) [Zhang and Li (2007), <DOI:10.1109/TEVC.2007.892759>] for quick assembling and testing of new algorithmic components, as well as easy replication of published MOEA/D proposals. The full framework is documented in a paper published in the Journal of Statistical Software [<doi:10.18637/jss.v092.i06>].

Maintained by Felipe Campelo. Last updated 2 years ago.

moead multiobjective-optimization

0.5 match 20 stars 6.30 score 40 scripts

alan-turing-institute

eider:Declarative Feature Extraction from Tabular Data Records

Extract features from tabular data in a declarative fashion, with a focus on processing medical records. Features are specified as JSON and are independently processed before being joined. Input data can be provided as CSV files or as data frames. This setup ensures that data is transformed in a modular and reproducible manner, and allows the same pipeline to be easily applied to new data.

Maintained by Camila Rangel Smith. Last updated 11 months ago.

hut23 hut23-1515

0.5 match 3 stars 6.26 score 10 scripts

molevolepid

SEEPS:Sequence evolution and epidemiological process simulator

A modular, modern simulation suite and toolkit for simulating transmission networks, phylogenies, and evolutionary pairwise distance matrices under different models and assumptions for viral/sequence evolution. While intially developed for HIV, SEEPS offers modular utilities for custom workflows for extension beyond HIV.

Maintained by Michael Kupperman. Last updated 2 months ago.

biological-sequences epidemiology evolution hiv simulation-framework

0.8 match 1 stars 3.95 score 6 scripts

taddallas

metacom:Analysis of the 'Elements of Metacommunity Structure'

Functions to analyze coherence, boundary clumping, and turnover following the pattern-based metacommunity analysis of Leibold and Mikkelson 2002 <doi:10.1034/j.1600-0706.2002.970210.x>. The package also includes functions to visualize ecological networks, and to calculate modularity as a replacement to boundary clumping.

Maintained by Tad Dallas. Last updated 2 years ago.

ecology metacommunity

0.5 match 11 stars 5.95 score 27 scripts 1 dependents

hope-data-science

akc:Automatic Knowledge Classification

A tidy framework for automatic knowledge classification and visualization. Currently, the core functionality of the framework is mainly supported by modularity-based clustering (community detection) in keyword co-occurrence network, and focuses on co-word analysis of bibliometric research. However, the designed functions in 'akc' are general, and could be extended to solve other tasks in text mining as well.

Maintained by Tian-Yuan Huang. Last updated 19 days ago.

0.5 match 15 stars 5.85 score 47 scripts

opendp

opendp:R Bindings for the OpenDP Library

The OpenDP Library is a modular collection of statistical algorithms that adhere to the definition of differential privacy. It can be used to build applications of privacy-preserving computations, using a number of different models of privacy.

Maintained by Stefano Iacus. Last updated 24 days ago.

differential-privacy dp-programming-framework opendp opendp-commons privacy rust cargo

0.5 match 343 stars 5.70 score 14 scripts

bioc

MetMashR:Metabolite Mashing with R

A package to merge, filter sort, organise and otherwise mash together metabolite annotation tables. Metabolite annotations can be imported from multiple sources (software) and combined using workflow steps based on S4 class templates derived from the `struct` package. Other modular workflow steps such as filtering, merging, splitting, normalisation and rest-api queries are included.

Maintained by Gavin Rhys Lloyd. Last updated 5 months ago.

workflowstep metabolomics kegg

0.5 match 2 stars 5.81 score 5 scripts

blasif

cocons:Covariate-Based Covariance Functions for Nonstationary Spatial Modeling

Estimation, prediction, and simulation of nonstationary Gaussian process with modular covariate-based covariance functions. Sources of nonstationarity, such as spatial mean, variance, geometric anisotropy, smoothness, and nugget, can be considered based on spatial characteristics. An induced compact-supported nonstationary covariance function is provided, enabling fast and memory-efficient computations when handling densely sampled domains.

Maintained by Federico Blasi. Last updated 2 months ago.

covariance-matrix cpp estimation gaussian-processes large-dataset nonstationarity optimization prediction cpp

0.5 match 3 stars 5.48 score 1 scripts

bioc

HELP:Tools for HELP data analysis

The package contains a modular pipeline for analysis of HELP microarray data, and includes graphical and mathematical tools with more general applications.

Maintained by Reid F. Thompson. Last updated 5 months ago.

cpgisland dnamethylation microarray twochannel dataimport qualitycontrol preprocessing visualization

0.5 match 5.18 score 76 scripts

gamlss-dev

gamlss2:GAMLSS Infrastructure for Flexible Distributional Regression

Next generation infrastructure for generalized additive models for location, scale, and shape (GAMLSS) and distributional regression more generally. The package provides a fresh reimplementaton of the classic 'gamlss' package while being more modular and facilitating the creation of advanced terms and models.

Maintained by Nikolaus Umlauf. Last updated 19 days ago.

0.5 match 7 stars 5.23 score 4 scripts 1 dependents

bioc

crisprVerse:Easily install and load the crisprVerse ecosystem for CRISPR gRNA design

The crisprVerse is a modular ecosystem of R packages developed for the design and manipulation of CRISPR guide RNAs (gRNAs). All packages share a common language and design principles. This package is designed to make it easy to install and load the crisprVerse packages in a single step. To learn more about the crisprVerse, visit <https://www.github.com/crisprVerse>.

Maintained by Jean-Philippe Fortin. Last updated 5 months ago.

crispr functionalgenomics genetarget crispr-analysis crispr-design crispr-target grna grna-sequence grna-sequences

0.5 match 13 stars 5.11 score 8 scripts

cran

Rfmtool:Fuzzy Measure Tools

Various tools for handling fuzzy measures, calculating Shapley value and interaction index, Choquet and Sugeno integrals, as well as fitting fuzzy measures to empirical data are provided. Construction of fuzzy measures from empirical data is done by solving a linear programming problem by using 'lpsolve' package, whose source in C adapted to the R environment is included. The description of the basic theory of fuzzy measures is in the manual in the Doc folder in this package. Please refer to the following: [1] <https://personal-sites.deakin.edu.au/~gleb/fmtools.html> [2] G. Beliakov, H. Bustince, T. Calvo, 'A Practical Guide to Averaging', Springer, (2016, ISBN: 978-3-319-24753-3). [3] G. Beliakov, S. James, J-Z. Wu, 'Discrete Fuzzy Measures', Springer, (2020, ISBN: 978-3-030-15305-2).

Maintained by Gleb Beliakov. Last updated 10 months ago.

cpp

2.0 match 1.30 score

jamespeapen

ceas:Cellular Energetics Analysis Software

Measuring cellular energetics is essential to understanding a matrix’s (e.g. cell, tissue or biofluid) metabolic state. The Agilent Seahorse machine is a common method to measure real-time cellular energetics, but existing analysis tools are highly manual or lack functionality. The Cellular Energetics Analysis Software (ceas) R package fills this analytical gap by providing modular and automated Seahorse data analysis and visualization using the methods described by Mookerjee et al. (2017) <doi:10.1074/jbc.m116.774471>.

Maintained by Rachel House. Last updated 3 months ago.

0.5 match 1 stars 5.08 score 3 scripts

piotrbajger

shinyreforms:Add Forms to your 'Shiny' App

Allows to create modular, reusable 'HTML' forms which can be embedded in your 'shiny' app with minimal effort. Features include conditional code execution on form submission, automatic input validation and input tooltips.

Maintained by Piotr Bajger. Last updated 2 years ago.

0.5 match 12 stars 4.78 score 4 scripts

bmoretz

dyn.log:Dynamic Logging for R Inspired by Configuration Driven Development

A comprehensive and dynamic configuration driven logging package for R. While there are several excellent logging solutions already in the R ecosystem, I always feel constrained in some way by each of them. Every project is designed differently to solve it's domain specific problem, and ultimately the utility of a logging solution is its ability to adapt to this design. This is the raison d'être for 'dyn.log': to provide a modular design, template mechanics and a configuration-based integration model, so that the logger can integrate deeply into your design, even though it knows nothing about it.

Maintained by Brandon Moretz. Last updated 3 years ago.

logging

0.5 match 1 stars 4.78 score 10 scripts

bioc

MAIT:Statistical Analysis of Metabolomic Data

The MAIT package contains functions to perform end-to-end statistical analysis of LC/MS Metabolomic Data. Special emphasis is put on peak annotation and in modular function design of the functions.

Maintained by Pol Sola-Santos. Last updated 5 months ago.

immunooncology massspectrometry metabolomics software

0.5 match 4.60 score 20 scripts

waternumbers

anomalous:Anomaly Detection using the CAPA and PELT Algorithms

Implimentations of the univariate CAPA <doi:10.1002/sam.11586> and PELT <doi:10.1080/01621459.2012.737745> algotithms along with various cost functions for different distributions and models. The modular design, using R6 classes, favour ease of extension (for example user written cost functions) over the performance of other implimentations (e.g. <doi:10.32614/CRAN.package.changepoint>, <doi:10.32614/CRAN.package.anomaly>).

Maintained by Paul Smith. Last updated 3 months ago.

cpp

0.5 match 4.61 score 18 scripts

joe-chelladurai

starry:Explore Data with Plots and Tables

Provides modular functions and applications for quickly generating plots and tables. Each modular function opens a graphical user interface providing the user with options to create and customise plots and tables.

Maintained by Joe Chelladurai. Last updated 2 years ago.

0.8 match 1 stars 2.70 score 1 scripts

bioc

mosbi:Molecular Signature identification using Biclustering

This package is a implementation of biclustering ensemble method MoSBi (Molecular signature Identification from Biclustering). MoSBi provides standardized interfaces for biclustering results and can combine their results with a multi-algorithm ensemble approach to compute robust ensemble biclusters on molecular omics data. This is done by computing similarity networks of biclusters and filtering for overlaps using a custom error model. After that, the louvain modularity it used to extract bicluster communities from the similarity network, which can then be converted to ensemble biclusters. Additionally, MoSBi includes several network visualization methods to give an intuitive and scalable overview of the results. MoSBi comes with several biclustering algorithms, but can be easily extended to new biclustering algorithms.

Maintained by Tim Daniel Rose. Last updated 5 months ago.

software statisticalmethod clustering network cpp

0.5 match 4.30 score 8 scripts

bioc

scHOT:single-cell higher order testing

Single cell Higher Order Testing (scHOT) is an R package that facilitates testing changes in higher order structure of gene expression along either a developmental trajectory or across space. scHOT is general and modular in nature, can be run in multiple data contexts such as along a continuous trajectory, between discrete groups, and over spatial orientations; as well as accommodate any higher order measurement such as variability or correlation. scHOT meaningfully adds to first order effect testing, such as differential expression, and provides a framework for interrogating higher order interactions from single cell data.

Maintained by Shila Ghazanfar. Last updated 5 months ago.

geneexpression rnaseq sequencing singlecell software transcriptomics

0.5 match 4.26 score 18 scripts

stla

cyclotomic:The Field of Cyclotomic Numbers

The cyclotomic numbers are complex numbers that can be thought of as the rational numbers extended with the roots of unity. They are represented exactly, enabling exact computations. They contain the Gaussian rationals (complex numbers with rational real and imaginary parts) as well as the square roots of all rational numbers. They also contain the sine and cosine of all rational multiples of pi. The algorithms implemented in this package are taken from the 'Haskell' package 'cyclotomic', whose algorithms are adapted from code by Martin Schoenert and Thomas Breuer in the 'GAP' project (<https://www.gap-system.org/>). Cyclotomic numbers have applications in number theory, algebraic geometry, algebraic number theory, coding theory, and in the theory of graphs and combinatorics. They have connections to the theory of modular functions and modular curves.

Maintained by Stéphane Laurent. Last updated 1 years ago.

arithmetic cyclotomic-numbers

0.8 match 1 stars 2.70 score 9 scripts

k-nadja

sdPrior:Scale-Dependent Hyperpriors in Structured Additive Distributional Regression

Utility functions for scale-dependent and alternative hyperpriors. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. Hyperpriors for all effects can be elicitated within the package. Including complex tensor product interaction terms and variable selection priors. The basic model is explained in in Klein and Kneib (2016) <doi:10.1214/15-BA983>.

Maintained by Nadja Klein. Last updated 6 years ago.

1.8 match 1.15 score 14 scripts

cboettig

EcoNetGen:Simulate and Sample from Ecological Interaction Networks

Randomly generate a wide range of interaction networks with specified size, average degree, modularity, and topological structure. Sample nodes and links from within simulated networks randomly, by degree, by module, or by abundance. Simulations and sampling routines are implemented in 'FORTRAN', providing efficient generation times even for large networks. Basic visualization methods also included. Algorithms implemented here are described in de Aguiar et al. (2017) <arXiv:1708.01242>.

Maintained by Carl Boettiger. Last updated 2 years ago.

fortran

0.5 match 9 stars 4.00 score 11 scripts

bioc

systemPipeTools:Tools for data visualization

systemPipeTools package extends the widely used systemPipeR (SPR) workflow environment with an enhanced toolkit for data visualization, including utilities to automate the data visualizaton for analysis of differentially expressed genes (DEGs). systemPipeTools provides data transformation and data exploration functions via scatterplots, hierarchical clustering heatMaps, principal component analysis, multidimensional scaling, generalized principal components, t-Distributed Stochastic Neighbor embedding (t-SNE), and MA and volcano plots. All these utilities can be integrated with the modular design of the systemPipeR environment that allows users to easily substitute any of these features and/or custom with alternatives.

Maintained by Daniela Cassol. Last updated 5 months ago.

infrastructure dataimport sequencing qualitycontrol reportwriting experimentaldesign clustering differentialexpression multidimensionalscaling principalcomponent

0.5 match 4.00 score 4 scripts

melinagall

shock:Slope Heuristic for Block-Diagonal Covariance Selection in High Dimensional Gaussian Graphical Models

Block-diagonal covariance selection for high dimensional Gaussian graphical models. The selection procedure is based on the slope heuristics.

Maintained by Melina Gallopin. Last updated 9 years ago.

2.0 match 1.00 score 6 scripts

bioc

KnowSeq:KnowSeq R/Bioc package: The Smart Transcriptomic Pipeline

KnowSeq proposes a novel methodology that comprises the most relevant steps in the Transcriptomic gene expression analysis. KnowSeq expects to serve as an integrative tool that allows to process and extract relevant biomarkers, as well as to assess them through a Machine Learning approaches. Finally, the last objective of KnowSeq is the biological knowledge extraction from the biomarkers (Gene Ontology enrichment, Pathway listing and Visualization and Evidences related to the addressed disease). Although the package allows analyzing all the data manually, the main strenght of KnowSeq is the possibilty of carrying out an automatic and intelligent HTML report that collect all the involved steps in one document. It is important to highligh that the pipeline is totally modular and flexible, hence it can be started from whichever of the different steps. KnowSeq expects to serve as a novel tool to help to the experts in the field to acquire robust knowledge and conclusions for the data and diseases to study.

Maintained by Daniel Castillo-Secilla. Last updated 5 months ago.

geneexpression differentialexpression genesetenrichment dataimport classification featureextraction sequencing rnaseq batcheffect normalization preprocessing qualitycontrol genetics transcriptomics microarray alignment pathways systemsbiology go immunooncology

0.5 match 3.30 score 5 scripts

cran

flux:Flux Rate Calculation from Dynamic Closed Chamber Measurements

Functions for the calculation of greenhouse gas flux rates from closed chamber concentration measurements. The package follows a modular concept: Fluxes can be calculated in just two simple steps or in several steps if more control in details is wanted. Additionally plot and preparation functions as well as functions for modelling gpp and reco are provided.

Maintained by Gerald Jurasinski. Last updated 3 years ago.

0.5 match 2 stars 3.21 score 3 dependents

txm676

nos:Compute Node Overlap and Segregation in Ecological Networks

Calculate NOS (node overlap and segregation) and the associated metrics described in Strona and Veech (2015) <DOI:10.1111/2041-210X.12395> and Strona et al. (2017, In Press). The functions provided in the package enable assessment of structural patterns ranging from complete node segregation to perfect nestedness in a variety of network types. In addition, they provide a measure of network modularity.

Maintained by Thomas J. Matthews. Last updated 12 months ago.

0.5 match 3.18 score 15 scripts

pariya

netShiny:Tool for Comparison and Visualization of Multiple Networks

We developed a comprehensive tool that helps with visualization and analysis of networks with the same variables across multiple factor levels. The 'netShiny' contains most of the popular network features such as centrality measures, modularity, and other summary statistics (e.g. clustering coefficient). It also contains known tools to look at the (dis)similarities between two networks, such as pairwise distance measures between networks, set operations on the nodes of the networks, distribution of the weights of the edges and a network representing the difference between two correlation matrices. The package 'netShiny' also contains tools to perform bootstrapping and find clusters in networks. See the 'netShiny' manual for more information, documentation and examples.

Maintained by Pariya Behrouzi. Last updated 3 years ago.

0.5 match 3.00 score 5 scripts

cran

AssocBin:Measuring Association with Recursive Binning

An iterative implementation of a recursive binary partitioning algorithm to measure pairwise dependence with a modular design that allows user specification of the splitting logic and stop criteria. Helper functions provide suggested versions of both and support visualization and the computation of summary statistics on final binnings. For a complete description of the functionality and algorithm, see Salahub and Oldford (2023) <doi:10.48550/arXiv.2311.08561>.

Maintained by Chris Salahub. Last updated 3 months ago.

0.5 match 2.60 score

cran

ConnectednessApproach:Connectedness Approach

The estimation of static and dynamic connectedness measures is created in a modular and user-friendly way. Besides, the time domain connectedness approaches, this package further allows to estimate the frequency connectedness approach, the joint spillover index and the extended joint connectedness approach. In addition, all connectedness frameworks can be based upon orthogonalized and generalized VAR, QVAR, LASSO VAR, Ridge VAR, Elastic Net VAR and TVP-VAR models. Furthermore, the package includes the conditional, decomposed and partial connectedness measures as well as the pairwise connectedness index, influence index and corrected total connectedness index. Finally, a battery of datasets are available allowing to replicate a variety of connectedness papers.

Maintained by David Gabauer. Last updated 16 days ago.

0.5 match 4 stars 2.60 score

cran

varitas:Variant Calling in Targeted Analysis Sequencing Data

Multi-caller variant analysis pipeline for targeted analysis sequencing (TAS) data. Features a modular, automated workflow that can start with raw reads and produces a user-friendly PDF summary and a spreadsheet containing consensus variant information.

Maintained by Adam Mills. Last updated 4 years ago.

0.5 match 2.30 score

uwemenzel

RMThreshold:Signal-Noise Separation in Random Matrices by using Eigenvalue Spectrum Analysis

An algorithm which can be used to determine an objective threshold for signal-noise separation in large random matrices (correlation matrices, mutual information matrices, network adjacency matrices) is provided. The package makes use of the results of Random Matrix Theory (RMT). The algorithm increments a suppositional threshold monotonically, thereby recording the eigenvalue spacing distribution of the matrix. According to RMT, that distribution undergoes a characteristic change when the threshold properly separates signal from noise. By using the algorithm, the modular structure of a matrix - or of the corresponding network - can be unraveled.

Maintained by Uwe Menzel. Last updated 9 years ago.

0.5 match 4 stars 2.16 score 18 scripts

ccook

ezmmek:Easy Michaelis-Menten Enzyme Kinetics

Serves as a platform for published fluorometric enzyme assay protocols. 'ezmmek' calibrates, calculates, and plots enzyme activities as they relate to the transformation of synthetic substrates. At present, 'ezmmek' implements two common protocols found in the literature, and is modular to accommodate additional protocols. Here, these protocols are referred to as the In-Sample Calibration (Hoppe, 1983; <doi:10.3354/meps011299>) and In-Buffer Calibration (German et al., 2011; <doi:10.1016/j.soilbio.2011.03.017>). protocols. By containing multiple protocols, 'ezmmek' aims to stimulate discussion about how to best optimize fluorometric enzyme assays. A standardized approach would make studies more comparable and reproducible.

Maintained by Christopher Cook. Last updated 5 years ago.

0.5 match 2.04 score 11 scripts

cran

pMEM:Predictive Moran's Eigenvector Maps

Calculation of Predictive Moran's eigenvector maps (pMEM), as defined by Guénard and Legendre (In Press) "Spatially-explicit predictions using spatial eigenvector maps" <doi:10.5281/zenodo.13356457>. Methods in Ecology and Evolution. This method enables scientists to predict the values of spatially-structured environmental variables. Multiple types of pMEM are defined, each one implemented on the basis of spatial weighting function taking a range parameter, and sometimes also a shape parameter. The code's modular nature enables programers to implement new pMEM by defining new spatial weighting functions.

Maintained by Guillaume Guénard. Last updated 6 months ago.

cpp

0.5 match 2.00 score 7 scripts

gvalentini58

RANKS:Ranking of Nodes with Kernelized Score Functions

Implementation of Kernelized score functions and other semi-supervised learning algorithms for node label ranking to analyze biomolecular networks. RANKS can be easily applied to a large set of different relevant problems in computational biology, ranging from automatic protein function prediction, to gene disease prioritization and drug repositioning, and more in general to any bioinformatics problem that can be formalized as a node label ranking problem in a graph. The modular nature of the implementation allows to experiment with different score functions and kernels and to easily compare the results with baseline network-based methods such as label propagation and random walk algorithms, as well as to enlarge the algorithmic scheme by adding novel user-defined score functions and kernels.

Maintained by Giorgio Valentini. Last updated 2 years ago.

0.5 match 1.90 score 7 scripts

alex-l-m

scquantum:Estimate Ploidy and Absolute Copy Number from Single Cell Sequencing

Given bincount data from single-cell copy number profiling (segmented or unsegmented), estimates ploidy, and uses the ploidy estimate to scale the data to absolute copy numbers. Uses the modular quantogram proposed by Kendall (1986) <doi:10.1002/0471667196.ess2129.pub2>, modified by weighting segments according to confidence, and quantifying confidence in the estimate using a theoretical quantogram. Includes optional fused-lasso segmentation with the algorithm in Johnson (2013) <doi:10.1080/10618600.2012.681238>, using the implementation from glmgen by Arnold, Sadhanala, and Tibshirani.

Maintained by Alexander Davis. Last updated 3 years ago.

0.5 match 1.70 score 3 scripts

weibzhan

ExplodeLayout:Calculate Exploded Coordinates Based on Original Node Coordinates and Node Clustering Membership

Current layout algorithms such as Kamada Kawai do not take into consideration disjoint clusters in a network, often resulting in a high overlap among the clusters, resulting in a visual “hairball” that often is uninterpretable. The ExplodeLayout algorithm takes as input (1) an edge list of a unipartite or bipartite network, (2) node layout coordinates (x, y) generated by a layout algorithm such as Kamada Kawai, (3) node cluster membership generated from a clustering algorithm such as modularity maximization, and (4) a radius to enable the node clusters to be “exploded” to reduce their overlap. The algorithm uses these inputs to generate new layout coordinates of the nodes which “explodes” the clusters apart, such that the edge lengths within the clusters are preserved, while the edge lengths between clusters are recalculated. The modified network layout with nodes and edges are displayed in two dimensions. The user can experiment with different explode radii to generate a layout which has sufficient separation of clusters, while reducing the overall layout size of the network. This package is a basic version of an earlier version called [epl]<https://github.com/UTMB-DIVA-Lab/epl> that searched for an optimal explode radius, and offered multiple ways to separate clusters in a network (Bhavnani et al(2017) <PMID: 28815099>). The example dataset is for a bipartite network, but the algorithm can work also for unipartite networks.

Maintained by Weibin Zhang. Last updated 3 years ago.

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arturotorres

EmiStatR:Emissions and Statistics in R for Wastewater and Pollutants in Combined Sewer Systems

Provides a fast and parallelised calculator to estimate combined wastewater emissions. It supports the planning and design of urban drainage systems, without the requirement of extensive simulation tools. The 'EmiStatR' package implements modular R methods. This enables to add new functionalities through the R framework.

Maintained by J.A. Torres-Matallana. Last updated 3 years ago.

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cran

rbc:Regression by Composition

Flexible statistical modelling using a modular framework for regression, in which groups of transformations are composed together and act on probability distributions.

Maintained by Daniel Farewell. Last updated 4 months ago.

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