Showing 119 of total 119 results (show query)
sachaepskamp
qgraph:Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation
Fork of qgraph - Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.
Maintained by Sacha Epskamp. Last updated 1 years ago.
69 stars 11.43 score 1.2k scripts 63 dependentssachaepskamp
semPlot:Path Diagrams and Visual Analysis of Various SEM Packages' Output
Path diagrams and visual analysis of various SEM packages' output.
Maintained by Sacha Epskamp. Last updated 3 years ago.
63 stars 10.64 score 2.1k scripts 13 dependentssachaepskamp
bootnet:Bootstrap Methods for Various Network Estimation Routines
Bootstrap methods to assess accuracy and stability of estimated network structures and centrality indices <doi:10.3758/s13428-017-0862-1>. Allows for flexible specification of any undirected network estimation procedure in R, and offers default sets for various estimation routines.
Maintained by Sacha Epskamp. Last updated 5 months ago.
32 stars 8.94 score 155 scripts 3 dependents
bioc
scp:Mass Spectrometry-Based Single-Cell Proteomics Data Analysis
Utility functions for manipulating, processing, and analyzing mass spectrometry-based single-cell proteomics data. The package is an extension to the 'QFeatures' package and relies on 'SingleCellExpirement' to enable single-cell proteomics analyses. The package offers the user the functionality to process quantitative table (as generated by MaxQuant, Proteome Discoverer, and more) into data tables ready for downstream analysis and data visualization.
Maintained by Christophe Vanderaa. Last updated 30 days ago.
geneexpressionproteomicssinglecellmassspectrometrypreprocessingcellbasedassaysbioconductormass-spectrometrysingle-cellsoftware
25 stars 8.94 score 115 scripts
jmbh
mgm:Estimating Time-Varying k-Order Mixed Graphical Models
Estimation of k-Order time-varying Mixed Graphical Models and mixed VAR(p) models via elastic-net regularized neighborhood regression. For details see Haslbeck & Waldorp (2020) <doi:10.18637/jss.v093.i08>.
Maintained by Jonas Haslbeck. Last updated 19 days ago.
29 stars 8.16 score 125 scripts 6 dependents
cwolock
survML:Tools for Flexible Survival Analysis Using Machine Learning
Statistical tools for analyzing time-to-event data using machine learning. Implements survival stacking for conditional survival estimation, standardized survival function estimation for current status data, and methods for algorithm-agnostic variable importance. See Wolock CJ, Gilbert PB, Simon N, and Carone M (2024) <doi:10.1080/10618600.2024.2304070>.
Maintained by Charles Wolock. Last updated 9 days ago.
17 stars 8.09 score 73 scripts 1 dependentsbioc
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 11 days ago.
networkinferencenetworkgeneregulationgeneexpressiontranscriptionmicroarraygraphandnetworkgene-regulatory-networktranscription-factors
105 stars 7.98 score
gateslab
gimme:Group Iterative Multiple Model Estimation
Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) <doi:10.1016/j.neuroimage.2012.06.026>.
Maintained by Kathleen M Gates. Last updated 9 days ago.
26 stars 7.61 score 53 scriptsbioc
IHW:Independent Hypothesis Weighting
Independent hypothesis weighting (IHW) is a multiple testing procedure that increases power compared to the method of Benjamini and Hochberg by assigning data-driven weights to each hypothesis. The input to IHW is a two-column table of p-values and covariates. The covariate can be any continuous-valued or categorical variable that is thought to be informative on the statistical properties of each hypothesis test, while it is independent of the p-value under the null hypothesis.
Maintained by Nikos Ignatiadis. Last updated 5 months ago.
immunooncologymultiplecomparisonrnaseq
7.25 score 264 scripts 2 dependents
yinanzheng
HIMA:High-Dimensional Mediation Analysis
Allows to estimate and test high-dimensional mediation effects based on advanced mediator screening and penalized regression techniques. Methods used in the package refer to Zhang H, Zheng Y, Zhang Z, Gao T, Joyce B, Yoon G, Zhang W, Schwartz J, Just A, Colicino E, Vokonas P, Zhao L, Lv J, Baccarelli A, Hou L, Liu L. Estimating and Testing High-dimensional Mediation Effects in Epigenetic Studies. Bioinformatics. (2016) <doi:10.1093/bioinformatics/btw351>. PMID: 27357171.
Maintained by Yinan Zheng. Last updated 2 months ago.
24 stars 7.22 score 23 scripts
sfcheung
semptools:Customizing Structural Equation Modelling Plots
Most function focus on specific ways to customize a graph. They use a 'qgraph' output as the first argument, and return a modified 'qgraph' object. This allows the functions to be chained by a pipe operator.
Maintained by Shu Fai Cheung. Last updated 3 months ago.
diagramgraphlavaanplotsemstructural-equation-modeling
7 stars 7.12 score 87 scriptsbioc
DEP:Differential Enrichment analysis of Proteomics data
This package provides an integrated analysis workflow for robust and reproducible analysis of mass spectrometry proteomics data for differential protein expression or differential enrichment. It requires tabular input (e.g. txt files) as generated by quantitative analysis softwares of raw mass spectrometry data, such as MaxQuant or IsobarQuant. Functions are provided for data preparation, filtering, variance normalization and imputation of missing values, as well as statistical testing of differentially enriched / expressed proteins. It also includes tools to check intermediate steps in the workflow, such as normalization and missing values imputation. Finally, visualization tools are provided to explore the results, including heatmap, volcano plot and barplot representations. For scientists with limited experience in R, the package also contains wrapper functions that entail the complete analysis workflow and generate a report. Even easier to use are the interactive Shiny apps that are provided by the package.
Maintained by Arne Smits. Last updated 5 months ago.
immunooncologyproteomicsmassspectrometrydifferentialexpressiondatarepresentation
7.10 score 628 scripts
alexchristensen
NetworkToolbox:Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis
Implements network analysis and graph theory measures used in neuroscience, cognitive science, and psychology. Methods include various filtering methods and approaches such as threshold, dependency (Kenett, Tumminello, Madi, Gur-Gershgoren, Mantegna, & Ben-Jacob, 2010 <doi:10.1371/journal.pone.0015032>), Information Filtering Networks (Barfuss, Massara, Di Matteo, & Aste, 2016 <doi:10.1103/PhysRevE.94.062306>), and Efficiency-Cost Optimization (Fallani, Latora, & Chavez, 2017 <doi:10.1371/journal.pcbi.1005305>). Brain methods include the recently developed Connectome Predictive Modeling (see references in package). Also implements several network measures including local network characteristics (e.g., centrality), community-level network characteristics (e.g., community centrality), global network characteristics (e.g., clustering coefficient), and various other measures associated with the reliability and reproducibility of network analysis.
Maintained by Alexander Christensen. Last updated 2 years ago.
23 stars 7.04 score 101 scripts 4 dependentsbioc
diffcoexp:Differential Co-expression Analysis
A tool for the identification of differentially coexpressed links (DCLs) and differentially coexpressed genes (DCGs). DCLs are gene pairs with significantly different correlation coefficients under two conditions. DCGs are genes with significantly more DCLs than by chance.
Maintained by Wenbin Wei. Last updated 5 months ago.
geneexpressiondifferentialexpressiontranscriptionmicroarrayonechanneltwochannelrnaseqsequencingcoverageimmunooncology
15 stars 6.89 score 37 scriptssachaepskamp
psychonetrics:Structural Equation Modeling and Confirmatory Network Analysis
Multi-group (dynamical) structural equation models in combination with confirmatory network models from cross-sectional, time-series and panel data <doi:10.31234/osf.io/8ha93>. Allows for confirmatory testing and fit as well as exploratory model search.
Maintained by Sacha Epskamp. Last updated 3 days ago.
51 stars 6.88 score 41 scripts 1 dependents
cvborkulo
IsingFit:Fitting Ising Models Using the ELasso Method
This network estimation procedure eLasso, which is based on the Ising model, combines l1-regularized logistic regression with model selection based on the Extended Bayesian Information Criterion (EBIC). EBIC is a fit measure that identifies relevant relationships between variables. The resulting network consists of variables as nodes and relevant relationships as edges. Can deal with binary data.
Maintained by Sacha Epskamp. Last updated 1 years ago.
10 stars 6.85 score 25 scripts 5 dependents
afukushima
DiffCorr:Analyzing and Visualizing Differential Correlation Networks in Biological Data
A method for identifying pattern changes between 2 experimental conditions in correlation networks (e.g., gene co-expression networks), which builds on a commonly used association measure, such as Pearson's correlation coefficient. This package includes functions to calculate correlation matrices for high-dimensional dataset and to test differential correlation, which means the changes in the correlation relationship among variables (e.g., genes and metabolites) between 2 experimental conditions.
Maintained by Atsushi Fukushima. Last updated 6 months ago.
5 stars 6.81 score 29 scripts 1 dependents
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 16 days ago.
6 stars 6.80 score 10 scriptsbioc
ideal:Interactive Differential Expression AnaLysis
This package provides functions for an Interactive Differential Expression AnaLysis of RNA-sequencing datasets, to extract quickly and effectively information downstream the step of differential expression. A Shiny application encapsulates the whole package. Support for reproducibility of the whole analysis is provided by means of a template report which gets automatically compiled and can be stored/shared.
Maintained by Federico Marini. Last updated 3 months ago.
immunooncologygeneexpressiondifferentialexpressionrnaseqsequencingvisualizationqualitycontrolguigenesetenrichmentreportwritingshinyappsbioconductordifferential-expressionreproducible-researchrna-seqrna-seq-analysisshinyuser-friendly
29 stars 6.78 score 5 scripts
paytonjjones
networktools:Tools for Identifying Important Nodes in Networks
Includes assorted tools for network analysis. Bridge centrality; goldbricker; MDS, PCA, & eigenmodel network plotting.
Maintained by Payton Jones. Last updated 1 months ago.
10 stars 6.75 score 93 scripts 5 dependents
vlyubchich
funtimes:Functions for Time Series Analysis
Nonparametric estimators and tests for time series analysis. The functions use bootstrap techniques and robust nonparametric difference-based estimators to test for the presence of possibly non-monotonic trends and for synchronicity of trends in multiple time series.
Maintained by Vyacheslav Lyubchich. Last updated 2 years ago.
7 stars 6.69 score 93 scripts
sonsoleslp
tna:Transition Network Analysis (TNA)
Provides tools for performing Transition Network Analysis (TNA) to study relational dynamics, including functions for building and plotting TNA models, calculating centrality measures, and identifying dominant events and patterns. TNA statistical techniques (e.g., bootstrapping and permutation tests) ensure the reliability of observed insights and confirm that identified dynamics are meaningful. See (Saqr et al., 2025) <doi:10.1145/3706468.3706513> for more details on TNA.
Maintained by Sonsoles López-Pernas. Last updated 4 days ago.
educational-data-mininglearning-analyticsmarkov-modeltemporal-analysis
4 stars 6.51 score 5 scripts
andreanini
idiolect:Forensic Authorship Analysis
Carry out comparative authorship analysis of disputed and undisputed texts within the Likelihood Ratio Framework for expressing evidence in forensic science. This package contains implementations of well-known algorithms for comparative authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta <doi:10.1080/09296174.2011.533591> or Koppel and Winter's (2014) Impostors Method <doi:10.1002/asi.22954>, as well as functions to measure their performance and to calibrate their outputs into Log-Likelihood Ratios.
Maintained by Andrea Nini. Last updated 22 days ago.
14 stars 6.12 score 3 scripts
jsakaluk
dySEM:Dyadic Structural Equation Modeling
Scripting of structural equation models via 'lavaan' for Dyadic Data Analysis, and helper functions for supplemental calculations, tabling, and model visualization. Current models supported include Dyadic Confirmatory Factor Analysis, the Actor–Partner Interdependence Model (observed and latent), the Common Fate Model (observed and latent), Mutual Influence Model (latent), and the Bifactor Dyadic Model (latent).
Maintained by John Sakaluk. Last updated 3 days ago.
6 stars 6.12 score 10 scriptsbioc
APAlyzer:A toolkit for APA analysis using RNA-seq data
Perform 3'UTR APA, Intronic APA and gene expression analysis using RNA-seq data.
Maintained by Ruijia Wang. Last updated 5 months ago.
sequencingrnaseqdifferentialexpressiongeneexpressiongeneregulationannotationdataimportsoftwareative-polyadenylationbioinformatics-toolrna-seq
9 stars 5.86 score 9 scripts
cfwp
rags2ridges:Ridge Estimation of Precision Matrices from High-Dimensional Data
Proper L2-penalized maximum likelihood estimators for precision matrices and supporting functions to employ these estimators in a graphical modeling setting. For details, see Peeters, Bilgrau, & van Wieringen (2022) <doi:10.18637/jss.v102.i04> and associated publications.
Maintained by Carel F.W. Peeters. Last updated 1 years ago.
c-plus-plusgraphical-modelsmachine-learningnetworksciencestatisticsopenblascpp
8 stars 5.60 score 46 scripts
benyamindsmith
ig.degree.betweenness:"Smith-Pittman Community Detection Algorithm for 'igraph' Objects (2024)"
Implements the "Smith-Pittman" community detection algorithm for network analysis using 'igraph' objects. This algorithm combines node degree and betweenness centrality measures to identify communities within networks, with a gradient evident in social partitioning. The package provides functions for community detection, visualization, and analysis of the resulting community structure. Methods are based on results from Smith, Pittman and Xu (2024) <doi:10.48550/arXiv.2411.01394>.
Maintained by Benjamin Smith. Last updated 14 days ago.
community-detection-algorithmsigraph
38 stars 5.50 score 11 scripts
avi-kenny
vaccine:Statistical Tools for Immune Correlates Analysis of Vaccine Clinical Trial Data
Various semiparametric and nonparametric statistical tools for immune correlates analysis of vaccine clinical trial data. This includes calculation of summary statistics and estimation of risk, vaccine efficacy, controlled effects (controlled risk and controlled vaccine efficacy), and mediation effects (natural direct effect, natural indirect effect, proportion mediated). See Gilbert P, Fong Y, Kenny A, and Carone, M (2022) <doi:10.1093/biostatistics/kxac024> and Fay MP and Follmann DA (2023) <doi:10.48550/arXiv.2208.06465>.
Maintained by Avi Kenny. Last updated 1 months ago.
4 stars 5.34 score 11 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.
4 stars 5.30 score 11 scripts 1 dependents
manueleleonelli
bnRep:A Repository of Bayesian Networks from the Academic Literature
A collection of Bayesian networks (discrete, Gaussian, and conditional linear Gaussian) collated from recent academic literature. The 'bnRep_summary' object provides an overview of the Bayesian networks in the repository and the package documentation includes details about the variables in each network. A Shiny app to explore the repository can be launched with 'bnRep_app()' and is available online at <https://manueleleonelli.shinyapps.io/bnRep>. For details see <https://github.com/manueleleonelli/bnRep>.
Maintained by Manuele Leonelli. Last updated 6 months ago.
6 stars 5.18 score 7 scripts
vandenman
NetworkComparisonTest:Statistical Comparison of Two Networks Based on Several Invariance Measures
This permutation based hypothesis test, suited for several types of data supported by the estimateNetwork function of the bootnet package (Epskamp & Fried, 2018), assesses the difference between two networks based on several invariance measures (network structure invariance, global strength invariance, edge invariance, several centrality measures, etc.). Network structures are estimated with l1-regularization. The Network Comparison Test is suited for comparison of independent (e.g., two different groups) and dependent samples (e.g., one group that is measured twice). See van Borkulo et al. (2021, in press; the final article will be available, upon publication, via its DOI: 10.1037/met0000476).
Maintained by Claudia van Borkulo. Last updated 3 years ago.
5.07 score 70 scriptsjmbh
mnet:Modeling Group Differences and Moderation Effects in Statistical Network Models
A toolbox for modeling manifest and latent group differences and moderation effects in various statistical network models.
Maintained by Jonas Haslbeck. Last updated 2 months ago.
4.91 score 18 scriptsbioc
PolySTest:PolySTest: Detection of differentially regulated features. Combined statistical testing for data with few replicates and missing values
The complexity of high-throughput quantitative omics experiments often leads to low replicates numbers and many missing values. We implemented a new test to simultaneously consider missing values and quantitative changes, which we combined with well-performing statistical tests for high confidence detection of differentially regulated features. The package contains functions to run the test and to visualize the results.
Maintained by Veit Schwämmle. Last updated 4 months ago.
massspectrometryproteomicssoftwaredifferentialexpression
4.86 score 12 scriptsbioc
FitHiC:Confidence estimation for intra-chromosomal contact maps
Fit-Hi-C is a tool for assigning statistical confidence estimates to intra-chromosomal contact maps produced by genome-wide genome architecture assays such as Hi-C.
Maintained by Ruyu Tan. Last updated 5 months ago.
4.78 score 2 scripts
jakobbossek
mcMST:A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem
Algorithms to approximate the Pareto-front of multi-criteria minimum spanning tree problems.
Maintained by Jakob Bossek. Last updated 2 years ago.
evolutionary-algorithmsmcmstminimum-spanning-treesmulti-objective-optimizationspanningtrees
4 stars 4.73 score 27 scripts
bioc
MetNet:Inferring metabolic networks from untargeted high-resolution mass spectrometry data
MetNet contains functionality to infer metabolic network topologies from quantitative data and high-resolution mass/charge information. Using statistical models (including correlation, mutual information, regression and Bayes statistics) and quantitative data (intensity values of features) adjacency matrices are inferred that can be combined to a consensus matrix. Mass differences calculated between mass/charge values of features will be matched against a data frame of supplied mass/charge differences referring to transformations of enzymatic activities. In a third step, the two levels of information are combined to form a adjacency matrix inferred from both quantitative and structure information.
Maintained by Thomas Naake. Last updated 5 months ago.
immunooncologymetabolomicsmassspectrometrynetworkregression
4.70 score 1 scripts
kylehamilton
lavaan.shiny:Latent Variable Analysis with Shiny
Interactive shiny application for working with different kinds of latent variable analysis, with the 'lavaan' package. Graphical output for models are provided and different estimators are supported.
Maintained by William Kyle Hamilton. Last updated 9 years ago.
10 stars 4.70 score 1 scripts
jongheepark
NetworkChange:Bayesian Package for Network Changepoint Analysis
Network changepoint analysis for undirected network data. The package implements a hidden Markov network change point model (Park and Sohn (2020)). Functions for break number detection using the approximate marginal likelihood and WAIC are also provided.
Maintained by Jong Hee Park. Last updated 3 years ago.
bayesianchangepointlatent-spacenetwork
5 stars 4.60 score 16 scriptsbioc
meshr:Tools for conducting enrichment analysis of MeSH
A set of annotation maps describing the entire MeSH assembled using data from MeSH.
Maintained by Koki Tsuyuzaki. Last updated 5 months ago.
annotationdatafunctionalannotationbioinformaticsstatisticsannotationmultiplecomparisonsmeshdb
4.56 score 9 scripts 1 dependents
karolinehuth
easybgm:Extracting and Visualizing Bayesian Graphical Models
Fit and visualize the results of a Bayesian analysis of networks commonly found in psychology. The package supports fitting cross-sectional network models fitted using the packages 'BDgraph', 'bgms' and 'BGGM'. The package provides the parameter estimates, posterior inclusion probabilities, inclusion Bayes factor, and the posterior density of the parameters. In addition, for 'BDgraph' and 'bgms' it allows to assess the posterior structure space. Furthermore, the package comes with an extensive suite for visualizing results.
Maintained by Karoline Huth. Last updated 5 months ago.
4.51 score 27 scriptsalexchristensen
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.
23 stars 4.51 score 28 scripts
pwarncke77
ResIN:Response Item Networks
Contains various tools to perform and visualize Response Item Networks ('ResIN's'). 'ResIN' binarizes ordered-categorical and qualitative response choices from (survey) data, calculates pairwise associations and maps the location of each item response as a node in a force-directed network. Please refer to <https://www.resinmethod.net/> for more details.
Maintained by Philip Warncke. Last updated 6 months ago.
4.48 score 3 scriptsbioc
oposSOM:Comprehensive analysis of transcriptome data
This package translates microarray expression data into metadata of reduced dimension. It provides various sample-centered and group-centered visualizations, sample similarity analyses and functional enrichment analyses. The underlying SOM algorithm combines feature clustering, multidimensional scaling and dimension reduction, along with strong visualization capabilities. It enables extraction and description of functional expression modules inherent in the data.
Maintained by Henry Loeffler-Wirth. Last updated 5 months ago.
geneexpressiondifferentialexpressiongenesetenrichmentdatarepresentationvisualizationcpp
4.48 score 7 scriptsbioc
epistasisGA:An R package to identify multi-snp effects in nuclear family studies using the GADGETS method
This package runs the GADGETS method to identify epistatic effects in nuclear family studies. It also provides functions for permutation-based inference and graphical visualization of the results.
Maintained by Michael Nodzenski. Last updated 5 months ago.
geneticssnpgeneticvariabilityopenblascpp
1 stars 4.48 score 5 scriptsbioc
Rtpca:Thermal proximity co-aggregation with R
R package for performing thermal proximity co-aggregation analysis with thermal proteome profiling datasets to analyse protein complex assembly and (differential) protein-protein interactions across conditions.
Maintained by Nils Kurzawa. Last updated 5 months ago.
4.46 score 29 scriptsbioc
HybridMTest:Hybrid Multiple Testing
Performs hybrid multiple testing that incorporates method selection and assumption evaluations into the analysis using empirical Bayes probability (EBP) estimates obtained by Grenander density estimation. For instance, for 3-group comparison analysis, Hybrid Multiple testing considers EBPs as weighted EBPs between F-test and H-test with EBPs from Shapiro Wilk test of normality as weigth. Instead of just using EBPs from F-test only or using H-test only, this methodology combines both types of EBPs through EBPs from Shapiro Wilk test of normality. This methodology uses then the law of total EBPs.
Maintained by Demba Fofana. Last updated 5 months ago.
geneexpressiongeneticsmicroarray
4.38 score 5 scripts 1 dependents
bioc
nethet:A bioconductor package for high-dimensional exploration of biological network heterogeneity
Package nethet is an implementation of statistical solid methodology enabling the analysis of network heterogeneity from high-dimensional data. It combines several implementations of recent statistical innovations useful for estimation and comparison of networks in a heterogeneous, high-dimensional setting. In particular, we provide code for formal two-sample testing in Gaussian graphical models (differential network and GGM-GSA; Stadler and Mukherjee, 2013, 2014) and make a novel network-based clustering algorithm available (mixed graphical lasso, Stadler and Mukherjee, 2013).
Maintained by Nicolas Staedler. Last updated 5 months ago.
4.30 score 7 scripts
jiangyouxiang
TestAnaAPP:A 'shiny' App for Test Analysis and Visualization
This application provides exploratory and confirmatory factor analysis, classical test theory, unidimensional and multidimensional item response theory, and continuous item response model analysis, through the 'shiny' interactive interface. In addition, it offers rich functionalities for visualizing and downloading results. Users can download figures, tables, and analysis reports via the interactive interface.
Maintained by Youxiang Jiang. Last updated 4 months ago.
4 stars 4.30 score 2 scripts
piyalkarum
rCNV:Detect Copy Number Variants from SNPs Data
Functions in this package will import filtered variant call format (VCF) files of SNPs data and generate data sets to detect copy number variants, visualize them and do downstream analyses with copy number variants(e.g. Environmental association analyses).
Maintained by Piyal Karunarathne. Last updated 26 days ago.
cnv-analysiscopy-number-variationgene-duplicationgeneticsgenomicslandscape-geneticssnpscpp
6 stars 4.26 score 4 scripts
psychbruce
PsychWordVec:Word Embedding Research Framework for Psychological Science
An integrative toolbox of word embedding research that provides: (1) a collection of 'pre-trained' static word vectors in the '.RData' compressed format <https://psychbruce.github.io/WordVector_RData.pdf>; (2) a series of functions to process, analyze, and visualize word vectors; (3) a range of tests to examine conceptual associations, including the Word Embedding Association Test <doi:10.1126/science.aal4230> and the Relative Norm Distance <doi:10.1073/pnas.1720347115>, with permutation test of significance; (4) a set of training methods to locally train (static) word vectors from text corpora, including 'Word2Vec' <arXiv:1301.3781>, 'GloVe' <doi:10.3115/v1/D14-1162>, and 'FastText' <arXiv:1607.04606>; (5) a group of functions to download 'pre-trained' language models (e.g., 'GPT', 'BERT') and extract contextualized (dynamic) word vectors (based on the R package 'text').
Maintained by Han-Wu-Shuang Bao. Last updated 1 years ago.
bertcosine-similarityfasttextglovegptlanguage-modelnatural-language-processingnlppretrained-modelspsychologysemantic-analysistext-analysistext-miningtsneword-embeddingsword-vectorsword2vecopenjdk
22 stars 4.04 score 10 scriptsbioc
splineTimeR:Time-course differential gene expression data analysis using spline regression models followed by gene association network reconstruction
This package provides functions for differential gene expression analysis of gene expression time-course data. Natural cubic spline regression models are used. Identified genes may further be used for pathway enrichment analysis and/or the reconstruction of time dependent gene regulatory association networks.
Maintained by Herbert Braselmann. Last updated 5 months ago.
geneexpressiondifferentialexpressiontimecourseregressiongenesetenrichmentnetworkenrichmentnetworkinferencegraphandnetwork
4.01 score 17 scripts
georgiosseitidis
viscomp:Visualize Multi-Component Interventions in Network Meta-Analysis
A set of functions providing several visualization tools for exploring the behavior of the components in a network meta-analysis of multi-component (complex) interventions: - components descriptive analysis - heat plot of the two-by-two component combinations - leaving one component combination out scatter plot - violin plot for specific component combinations' effects - density plot for components' effects - waterfall plot for the interventions' effects that differ by a certain component combination - network graph of components - rank heat plot of components for multiple outcomes. The implemented tools are described by Seitidis et al. (2023) <doi:10.1002/jrsm.1617>.
Maintained by Georgios Seitidis. Last updated 2 years ago.
cnmacomplexmulticomponentnmavisualization
2 stars 4.00 score 6 scriptsbioc
scTensor:Detection of cell-cell interaction from single-cell RNA-seq dataset by tensor decomposition
The algorithm is based on the non-negative tucker decomposition (NTD2) of nnTensor.
Maintained by Koki Tsuyuzaki. Last updated 5 months ago.
dimensionreductionsinglecellsoftwaregeneexpression
4.00 score 2 scriptsbioc
OVESEG:OVESEG-test to detect tissue/cell-specific markers
An R package for multiple-group comparison to detect tissue/cell-specific marker genes among subtypes. It provides functions to compute OVESEG-test statistics, derive component weights in the mixture null distribution model and estimate p-values from weightedly aggregated permutations. Obtained posterior probabilities of component null hypotheses can also portrait all kinds of upregulation patterns among subtypes.
Maintained by Lulu Chen. Last updated 5 months ago.
softwaremultiplecomparisoncellbiologygeneexpressioncpp
1 stars 4.00 score 2 scripts
ttacail
isobxr:Stable Isotope Box Modelling in R
A set of functions to run simple and composite box-models to describe the dynamic or static distribution of stable isotopes in open or closed systems. The package also allows the sweeping of many parameters in both static and dynamic conditions. The mathematical models used in this package are derived from Albarede, 1995, Introduction to Geochemical Modelling, Cambridge University Press, Cambridge <doi:10.1017/CBO9780511622960>.
Maintained by Theo Tacail. Last updated 11 months ago.
1 stars 4.00 score 2 scriptsbioc
metapone:Conducts pathway test of metabolomics data using a weighted permutation test
The package conducts pathway testing from untargetted metabolomics data. It requires the user to supply feature-level test results, from case-control testing, regression, or other suitable feature-level tests for the study design. Weights are given to metabolic features based on how many metabolites they could potentially match to. The package can combine positive and negative mode results in pathway tests.
Maintained by Tianwei Yu. Last updated 5 months ago.
technologymassspectrometrymetabolomicspathways
4.00 score 9 scriptsmanueleleonelli
bnmonitor:An Implementation of Sensitivity Analysis in Bayesian Networks
An implementation of sensitivity and robustness methods in Bayesian networks in R. It includes methods to perform parameter variations via a variety of co-variation schemes, to compute sensitivity functions and to quantify the dissimilarity of two Bayesian networks via distances and divergences. It further includes diagnostic methods to assess the goodness of fit of a Bayesian networks to data, including global, node and parent-child monitors. Reference: M. Leonelli, R. Ramanathan, R.L. Wilkerson (2022) <doi:10.1016/j.knosys.2023.110882>.
Maintained by Manuele Leonelli. Last updated 6 months ago.
3 stars 3.92 score 14 scriptsalexchristensen
latentFactoR:Data Simulation Based on Latent Factors
Generates data based on latent factor models. Data can be continuous, polytomous, dichotomous, or mixed. Skews, cross-loadings, wording effects, population errors, and local dependencies can be added. All parameters can be manipulated. Data categorization is based on Garrido, Abad, and Ponsoda (2011) <doi:10.1177/0013164410389489>.
Maintained by Alexander Christensen. Last updated 8 months ago.
3 stars 3.88 score 2 scriptspaytonjjones
networktree:Recursive Partitioning of Network Models
Network trees recursively partition the data with respect to covariates. Two network tree algorithms are available: model-based trees based on a multivariate normal model and nonparametric trees based on covariance structures. After partitioning, correlation-based networks (psychometric networks) can be fit on the partitioned data. For details see Jones, Mair, Simon, & Zeileis (2020) <doi:10.1007/s11336-020-09731-4>.
Maintained by Payton Jones. Last updated 3 years ago.
network-analysispsychometricstree-models
13 stars 3.85 score 11 scripts
bioc
DMCHMM:Differentially Methylated CpG using Hidden Markov Model
A pipeline for identifying differentially methylated CpG sites using Hidden Markov Model in bisulfite sequencing data. DNA methylation studies have enabled researchers to understand methylation patterns and their regulatory roles in biological processes and disease. However, only a limited number of statistical approaches have been developed to provide formal quantitative analysis. Specifically, a few available methods do identify differentially methylated CpG (DMC) sites or regions (DMR), but they suffer from limitations that arise mostly due to challenges inherent in bisulfite sequencing data. These challenges include: (1) that read-depths vary considerably among genomic positions and are often low; (2) both methylation and autocorrelation patterns change as regions change; and (3) CpG sites are distributed unevenly. Furthermore, there are several methodological limitations: almost none of these tools is capable of comparing multiple groups and/or working with missing values, and only a few allow continuous or multiple covariates. The last of these is of great interest among researchers, as the goal is often to find which regions of the genome are associated with several exposures and traits. To tackle these issues, we have developed an efficient DMC identification method based on Hidden Markov Models (HMMs) called “DMCHMM” which is a three-step approach (model selection, prediction, testing) aiming to address the aforementioned drawbacks.
Maintained by Farhad Shokoohi. Last updated 5 months ago.
differentialmethylationsequencinghiddenmarkovmodelcoverage
3.78 score 3 scripts
sciurus365
quadVAR:Quadratic Vector Autoregression
Estimate quadratic vector autoregression models with the strong hierarchy using the Regularization Algorithm under Marginality Principle (RAMP) by Hao et al. (2018) <doi:10.1080/01621459.2016.1264956>, compare the performance with linear models, and construct networks with partial derivatives.
Maintained by Jingmeng Cui. Last updated 2 months ago.
3.78 score 3 scriptsbioc
les:Identifying Differential Effects in Tiling Microarray Data
The 'les' package estimates Loci of Enhanced Significance (LES) in tiling microarray data. These are regions of regulation such as found in differential transcription, CHiP-chip, or DNA modification analysis. The package provides a universal framework suitable for identifying differential effects in tiling microarray data sets, and is independent of the underlying statistics at the level of single probes.
Maintained by Julian Gehring. Last updated 5 months ago.
microarraydifferentialexpressionchipchipdnamethylationtranscription
3.78 score 3 scripts 1 dependents
xinkaidupsy
IVPP:Invariance Partial Pruning Test
An implementation of the Invariance Partial Pruning (IVPP) approach described in Du, X., Johnson, S. U., Epskamp, S. (2025) The Invariance Partial Pruning Approach to The Network Comparison in Longitudinal Data. IVPP is a two-step method that first test for global network structural difference with invariance test and then inspect specific edge difference with partial pruning.
Maintained by Xinkai Du. Last updated 4 days ago.
3.74 score 7 scripts
jglev
veccompare:Perform Set Operations on Vectors, Automatically Generating All n-Wise Comparisons, and Create Markdown Output
Automates set operations (i.e., comparisons of overlap) between multiple vectors. It also contains a function for automating reporting in 'RMarkdown', by generating markdown output for easy analysis, as well as an 'RMarkdown' template for use with 'RStudio'.
Maintained by Jacob Gerard Levernier. Last updated 8 years ago.
8 stars 3.60 score 10 scripts
mihaiconstantin
powerly:Sample Size Analysis for Psychological Networks and More
An implementation of the sample size computation method for network models proposed by Constantin et al. (2021) <doi:10.31234/osf.io/j5v7u>. The implementation takes the form of a three-step recursive algorithm designed to find an optimal sample size given a model specification and a performance measure of interest. It starts with a Monte Carlo simulation step for computing the performance measure and a statistic at various sample sizes selected from an initial sample size range. It continues with a monotone curve-fitting step for interpolating the statistic across the entire sample size range. The final step employs stratified bootstrapping to quantify the uncertainty around the fitted curve.
Maintained by Mihai Constantin. Last updated 2 years ago.
network-modelspower-analysispsychologysample-size-calculation
8 stars 3.60 score 3 scripts
henry-heppe
adproclus:Additive Profile Clustering Algorithms
Obtain overlapping clustering models for object-by-variable data matrices using the Additive Profile Clustering (ADPROCLUS) method. Also contains the low dimensional ADPROCLUS method for simultaneous dimension reduction and overlapping clustering. For reference see Depril, Van Mechelen, Mirkin (2008) <doi:10.1016/j.csda.2008.04.014> and Depril, Van Mechelen, Wilderjans (2012) <doi:10.1007/s00357-012-9112-5>.
Maintained by Henry Heppe. Last updated 7 months ago.
2 stars 3.60 score 2 scriptsbioc
GSRI:Gene Set Regulation Index
The GSRI package estimates the number of differentially expressed genes in gene sets, utilizing the concept of the Gene Set Regulation Index (GSRI).
Maintained by Julian Gehring. Last updated 5 months ago.
microarraytranscriptiondifferentialexpressiongenesetenrichmentgeneregulation
3.30 score 2 scripts
cran
sda:Shrinkage Discriminant Analysis and CAT Score Variable Selection
Provides an efficient framework for high-dimensional linear and diagonal discriminant analysis with variable selection. The classifier is trained using James-Stein-type shrinkage estimators and predictor variables are ranked using correlation-adjusted t-scores (CAT scores). Variable selection error is controlled using false non-discovery rates or higher criticism.
Maintained by Korbinian Strimmer. Last updated 3 years ago.
3.21 score 3 dependentscran
GeneNet:Modeling and Inferring Gene Networks
Analyzes gene expression (time series) data with focus on the inference of gene networks. In particular, GeneNet implements the methods of Schaefer and Strimmer (2005a,b,c) and Opgen-Rhein and Strimmer (2006, 2007) for learning large-scale gene association networks (including assignment of putative directions).
Maintained by Korbinian Strimmer. Last updated 3 years ago.
3.18 score 5 dependents
skranz
phack:Detecting p-Hacking using Elliot et al. (2022)
Implements the tests from Elliot et al. (2022) for detecting p-Hacking. The package is essentially a simple wrapper to the code provided in the code and data supplement of the article, with some cosmetical changes. The original code can be found in the code and data supplement of the article. s References Elliott, G., Kudrin, N., & Wüthrich, K. (2022). Detecting p‐Hacking. Econometrica, 90(2), 887-906.
Maintained by Sebastian Kranz. Last updated 3 years ago.
2 stars 3.00 score
pilacuan-bonete-luis
LDABiplots:Biplot Graphical Interface for LDA Models
Contains the development of a tool that provides a web-based graphical user interface (GUI) to perform Biplots representations from a scraping of news from digital newspapers under the Bayesian approach of Latent Dirichlet Assignment (LDA) and machine learning algorithms. Contains LDA methods described by Blei , David M., Andrew Y. Ng and Michael I. Jordan (2003) <https://jmlr.org/papers/volume3/blei03a/blei03a.pdf>, and Biplot methods described by Gabriel K.R(1971) <doi:10.1093/biomet/58.3.453> and Galindo-Villardon P(1986) <https://diarium.usal.es/pgalindo/files/2012/07/Questiio.pdf>.
Maintained by Luis Pilacuan-Bonete. Last updated 3 years ago.
3.00 score 4 scripts
mjafin
GeneCycle:Identification of Periodically Expressed Genes
The GeneCycle package implements the approaches of Wichert et al. (2004) <doi:10.1093/bioinformatics/btg364>, Ahdesmaki et al. (2005) <doi:10.1186/1471-2105-6-117> and Ahdesmaki et al. (2007) <DOI:10.1186/1471-2105-8-233> for detecting periodically expressed genes from gene expression time series data.
Maintained by Miika Ahdesmaki. Last updated 4 years ago.
1 stars 2.81 score 64 scripts
tswanson222
modnets:Modeling Moderated Networks
Methods for modeling moderator variables in cross-sectional, temporal, and multi-level networks. Includes model selection techniques and a variety of plotting functions. Implements the methods described by Swanson (2020) <https://www.proquest.com/openview/d151ab6b93ad47e3f0d5e59d7b6fd3d3>.
Maintained by Trevor Swanson. Last updated 3 years ago.
2.70 score 6 scripts
anastasiou-andreas
ccid:Cross-Covariance Isolate Detect: a New Change-Point Method for Estimating Dynamic Functional Connectivity
Provides efficient implementation of the Cross-Covariance Isolate Detect (CCID) methodology for the estimation of the number and location of multiple change-points in the second-order (cross-covariance or network) structure of multivariate, possibly high-dimensional time series. The method is motivated by the detection of change points in functional connectivity networks for functional magnetic resonance imaging (fMRI), electroencephalography (EEG), magentoencephalography (MEG) and electrocorticography (ECoG) data. The main routines in the package have been extensively tested on fMRI data. For details on the CCID methodology, please see Anastasiou et al (2020).
Maintained by Andreas Anastasiou. Last updated 4 years ago.
2.70 score 2 scripts
talegari
ggisotonic:'ggplot2' Friendly Isotonic or Monotonic Regression Curves
Provides stat_isotonic() to add weighted univariate isotonic regression curves.
Maintained by Komala Sheshachala Srikanth. Last updated 3 years ago.
1 stars 2.70 score 3 scripts
yujian-wu
MonotoneHazardRatio:Nonparametric Estimation and Inference of a Monotone Hazard Ratio Function
A tool for nonparametric estimation and inference of a non-decreasing monotone hazard ratio from a right censored survival dataset. The estimator is based on a generalized Grenander typed estimator, and the inference procedure relies on direct plugin estimation of a first order derivative. More details please refer to the paper "Nonparametric inference under a monotone hazard ratio order" by Y. Wu and T. Westling (2023).
Maintained by Yujian Wu. Last updated 5 months ago.
2.70 score 2 scripts
williamsandra
GIMMEgVAR:Group Iterative Multiple Model Estimation with 'graphicalVAR'
Data-driven approach for arriving at person-specific time series models from within a Graphical Vector Autoregression (VAR) framework. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. All estimates are obtained uniquely for each individual in the final models. The method for the 'graphicalVAR' approach is found in Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.
Maintained by Sandra Williams Lee. Last updated 11 months ago.
2.70 score
umich-cphds
medScan:Large Scale Single Mediator Hypothesis Testing
A collection of methods for large scale single mediator hypothesis testing. The six included methods for testing the mediation effect are Sobel's test, Max P test, joint significance test under the composite null hypothesis, high dimensional mediation testing, divide-aggregate composite null test, and Sobel's test under the composite null hypothesis. Du et al (2023) <doi:10.1002/gepi.22510>.
Maintained by Michael Kleinsasser. Last updated 1 years ago.
2.70 score 5 scripts
caromillat
MultiGroupO:MultiGroup Method and Simulation Data Analysis
Two method new of multigroup and simulation of data. The first technique called multigroup PCA (mgPCA) this multivariate exploration approach that has the idea of considering the structure of groups and / or different types of variables. On the other hand, the second multivariate technique called Multigroup Dimensionality Reduction (MDR) it is another multivariate exploration method that is based on projections. In addition, a method called Single Dimension Exploration (SDE) was incorporated for to analyze the exploration of the data. It could help us in a better way to observe the behavior of the multigroup data with certain variables of interest.
Maintained by Carolina Millap/an. Last updated 9 months ago.
2.60 score 4 scriptscran
mlVAR:Multi-Level Vector Autoregression
Estimates the multi-level vector autoregression model on time-series data. Three network structures are obtained: temporal networks, contemporaneous networks and between-subjects networks.
Maintained by Sacha Epskamp. Last updated 1 years ago.
2.56 score 2 dependentscran
graphicalVAR:Graphical VAR for Experience Sampling Data
Estimates within and between time point interactions in experience sampling data, using the Graphical vector autoregression model in combination with regularization. See also Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.
Maintained by Sacha Epskamp. Last updated 1 years ago.
2 stars 2.48 score 5 dependentscran
st:Shrinkage t Statistic and Correlation-Adjusted t-Score
Implements the "shrinkage t" statistic introduced in Opgen-Rhein and Strimmer (2007) <DOI:10.2202/1544-6115.1252> and a shrinkage estimate of the "correlation-adjusted t-score" (CAT score) described in Zuber and Strimmer (2009) <DOI:10.1093/bioinformatics/btp460>. It also offers a convenient interface to a number of other regularized t-statistics commonly employed in high-dimensional case-control studies.
Maintained by Korbinian Strimmer. Last updated 3 years ago.
2.43 score 1 dependents
rwehrens
BioMark:Find Biomarkers in Two-Class Discrimination Problems
Variable selection methods are provided for several classification methods: the lasso/elastic net, PCLDA, PLSDA, and several t-tests. Two approaches for selecting cutoffs can be used, one based on the stability of model coefficients under perturbation, and the other on higher criticism.
Maintained by Ron Wehrens. Last updated 10 years ago.
2.32 score 21 scripts
aybekec
RSP:'shiny' Applications for Statistical and Psychometric Analysis
Toolbox with 'shiny' applications for widely used psychometric methods. Those methods include following analysis: Item analysis, item response theory calibration, principal component analysis, confirmatory factor analysis - structural equation modeling, generating simulated data. References: Chalmers (2012, <doi:10.18637/jss.v048.i06>); Revelle (2022, <https://CRAN.R-project.org/package=psych Version = 2.2.9.>); Rosseel (2012, <doi:10.18637/jss.v048.i02>); Magis & Raiche (2012, <doi:10.18637/jss.v048.i08>); Magis & Barrada (2017, <doi:10.18637/jss.v076.c01>).
Maintained by Eren Can Aybek. Last updated 2 years ago.
2.28 score 19 scripts
cran
SOHPIE:Statistical Approach via Pseudo-Value Information and Estimation
'SOHPIE' (pronounced as SOFIE) is a novel pseudo-value regression approach for differential co-abundance network analysis of microbiome data, which can include additional clinical covariate in the model. The full methodological details can be found in Ahn S and Datta S (2023) <arXiv:2303.13702v1>.
Maintained by Seungjun Ahn. Last updated 1 years ago.
2.00 scorecran
SMAHP:Survival Mediation Analysis of High-Dimensional Proteogenomic Data
SMAHP (pronounced as SOO-MAP) is a novel multi-omics framework for causal mediation analysis of high-dimensional proteogenomic data with survival outcomes. The full methodological details can be found in our recent preprint by Ahn S et al. (2025) <doi:10.48550/arXiv.2503.08606>.
Maintained by Weijia Fu. Last updated 6 days ago.
2.00 score
giuliocostantini
IATscores:Implicit Association Test Scores Using Robust Statistics
Compute several variations of the Implicit Association Test (IAT) scores, including the D scores (Greenwald, Nosek, Banaji, 2003, <doi:10.1037/0022-3514.85.2.197>) and the new scores that were developed using robust statistics (Richetin, Costantini, Perugini, and Schonbrodt, 2015, <doi:10.1371/journal.pone.0129601>).
Maintained by Giulio Costantini. Last updated 5 years ago.
2.00 score 6 scriptscran
MariNET:Build Network Based on Linear Mixed Models from EHRs
Analyzing longitudinal clinical data from Electronic Health Records (EHRs) using linear mixed models (LMM) and visualizing the results as networks. It includes functions for fitting LMM, normalizing adjacency matrices, and comparing networks. The package is designed for researchers in clinical and biomedical fields who need to model longitudinal data and explore relationships between variables For more details see Bates et al. (2015) <doi:10.18637/jss.v067.i01>.
Maintained by Vargas-Fernández Marina. Last updated 8 days ago.
2.00 score
dcauseur
FADA:Variable Selection for Supervised Classification in High Dimension
The functions provided in the FADA (Factor Adjusted Discriminant Analysis) package aim at performing supervised classification of high-dimensional and correlated profiles. The procedure combines a decorrelation step based on a factor modeling of the dependence among covariates and a classification method. The available methods are Lasso regularized logistic model (see Friedman et al. (2010)), sparse linear discriminant analysis (see Clemmensen et al. (2011)), shrinkage linear and diagonal discriminant analysis (see M. Ahdesmaki et al. (2010)). More methods of classification can be used on the decorrelated data provided by the package FADA.
Maintained by David Causeur. Last updated 5 years ago.
1.90 score 6 scripts
cran
iclogcondist:Log-Concave Distribution Estimation with Interval-Censored Data
We consider the non-parametric maximum likelihood estimation of the underlying distribution function, assuming log-concavity, based on mixed-case interval-censored data. The algorithm implemented is base on Chi Wing Chu, Hok Kan Ling and Chaoyu Yuan (2024, <doi:10.48550/arXiv.2411.19878>).
Maintained by Chaoyu Yuan. Last updated 4 months ago.
1.70 score
gsun2018
TBEST:Tree Branches Evaluated Statistically for Tightness
Our method introduces mathematically well-defined measures for tightness of branches in a hierarchical tree. Statistical significance of the findings is determined, for all branches of the tree, by performing permutation tests, optionally with generalized Pareto p-value estimation.
Maintained by Guoli Sun. Last updated 3 years ago.
1.30 score 8 scripts
wjzhong
mDAG:Inferring Causal Network from Mixed Observational Data Using a Directed Acyclic Graph
Learning a mixed directed acyclic graph based on both continuous and categorical data.
Maintained by Wujuan Zhong. Last updated 6 years ago.
1.30 score 5 scripts
chiranjibsbioinfo
EGRNi:Ensemble Gene Regulatory Network Inference
Gene regulatory network constructed using combined score obtained from individual network inference method. The combined score measures the significance of edges in the ensemble network. Fisher's weighted method has been implemented to combine the outcomes of different methods based on the probability values. The combined score follows chi-square distribution with 2n degrees of freedom. <doi:10.22271/09746315.2020.v16.i3.1358>.
Maintained by Chiranjib Sarkar. Last updated 2 years ago.
1.18 score 15 scripts
zzheng68
MixTwice:Large-Scale Hypothesis Testing by Variance Mixing
Implements large-scale hypothesis testing by variance mixing. It takes two statistics per testing unit -- an estimated effect and its associated squared standard error -- and fits a nonparametric, shape-constrained mixture separately on two latent parameters. It reports local false discovery rates (lfdr) and local false sign rates (lfsr). Manuscript describing algorithm of MixTwice: Zheng et al(2021) <doi: 10.1093/bioinformatics/btab162>.
Maintained by Zihao Zheng. Last updated 3 years ago.
1.00 score 1 scriptscran
carSurv:Correlation-Adjusted Regression Survival (CARS) Scores
Contains functions to estimate the Correlation-Adjusted Regression Survival (CARS) Scores. The method is described in Welchowski, T. and Zuber, V. and Schmid, M., (2018), Correlation-Adjusted Regression Survival Scores for High-Dimensional Variable Selection, <arXiv:1802.08178>.
Maintained by Thomas Welchowski. Last updated 7 years ago.
1.00 scorecran
vampyr:Factor Analysis Controlling the Effects of Response Bias
Vampirize the response biases from a dataset! Performs factor analysis controlling the effects of social desirability and acquiescence using the method described in Ferrando, Lorenzo-Seva & Chico (2009) <doi:10.1080/10705510902751374>.
Maintained by David Navarro-Gonzalez. Last updated 4 years ago.
1.00 scorecran
lvnet:Latent Variable Network Modeling
Estimate, fit and compare Structural Equation Models (SEM) and network models (Gaussian Graphical Models; GGM) using OpenMx. Allows for two possible generalizations to include GGMs in SEM: GGMs can be used between latent variables (latent network modeling; LNM) or between residuals (residual network modeling; RNM). For details, see Epskamp, Rhemtulla and Borsboom (2017) <doi:10.1007/s11336-017-9557-x>.
Maintained by Sacha Epskamp. Last updated 6 years ago.
1.00 scorecran
hdthreshold:Inference on Many Jumps in Nonparametric Panel Regression Models
Provides uniform testing procedures for existence and heterogeneity of threshold effects in high-dimensional nonparametric panel regression models. The package accompanies the paper Chen, Keilbar, Su and Wang (2023) "Inference on many jumps in nonparametric panel regression models". arXiv preprint <doi:10.48550/arXiv.2312.01162>.
Maintained by Georg Keilbar. Last updated 3 months ago.
1.00 scorecran
nlnet:Nonlinear Network, Clustering, and Variable Selection Based on DCOL
It includes four methods: DCOL-based K-profiles clustering, non-linear network reconstruction, non-linear hierarchical clustering, and variable selection for generalized additive model. References: Tianwei Yu (2018)<DOI: 10.1002/sam.11381>; Haodong Liu and others (2016)<DOI: 10.1371/journal.pone.0158247>; Kai Wang and others (2015)<DOI: 10.1155/2015/918954>; Tianwei Yu and others (2010)<DOI: 10.1109/TCBB.2010.73>.
Maintained by Tianwei Yu. Last updated 4 years ago.
1 stars 1.00 scorecran
EstimateGroupNetwork:Perform the Joint Graphical Lasso and Selects Tuning Parameters
Can be used to simultaneously estimate networks (Gaussian Graphical Models) in data from different groups or classes via Joint Graphical Lasso. Tuning parameters are selected via information criteria (AIC / BIC / extended BIC) or cross validation.
Maintained by Giulio Costantini. Last updated 4 years ago.
1 stars 1.00 score
kartikeyabolar
semdrw:'SEM Shiny'
Interactive 'shiny' application for working with Structural Equation Modelling technique. Runtime examples are provided in the package function as well as at <https://kartikeyab.shinyapps.io/semwebappk/> .
Maintained by Kartikeya Bolar. Last updated 6 years ago.
1.00 score 1 scriptscran
NetworkComparr:Statistical Comparison of Networks
A permutation-based hypothesis test for statistical comparison of two networks based on the invariance measures of the R package 'NetworkComparisonTest' by van Borkulo et al. (2022), <doi:10.1037/met0000476>: network structure invariance, global strength invariance, edge invariance, and various centrality measures. Edgelists from dependent or independent samples are used as input. These edgelists are generated from concept maps and summed into two comparable group networks. The networks can be directed or undirected.
Maintained by Lara Trani. Last updated 2 years ago.
1.00 score