R-universe search: exports:combine

Various R programming tools for data manipulation, including medical unit conversions, combining objects, character vector operations, factor manipulation, obtaining information about R objects, generating fixed-width format files, extracting components of date & time objects, operations on columns of data frames, matrix operations, operations on vectors, operations on data frames, value of last evaluated expression, and a resample() wrapper for sample() that ensures consistent behavior for both scalar and vector arguments.

Maintained by Arni Magnusson. Last updated 3 months ago.

9 stars 13.62 score 4.5k scripts 124 dependents

bioc

minfi:Analyze Illumina Infinium DNA methylation arrays

Tools to analyze & visualize Illumina Infinium methylation arrays.

Maintained by Kasper Daniel Hansen. Last updated 4 months ago.

immunooncology dnamethylation differentialmethylation epigenetics microarray methylationarray multichannel twochannel dataimport normalization preprocessing qualitycontrol

60 stars 12.82 score 996 scripts 27 dependents

bioc

EBImage:Image processing and analysis toolbox for R

EBImage provides general purpose functionality for image processing and analysis. In the context of (high-throughput) microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and facilitates the use of other tools in the R environment for signal processing, statistical modeling, machine learning and visualization with image data.

Maintained by Andrzej Oleś. Last updated 5 months ago.

visualization bioinformatics image-analysis image-processing cpp

71 stars 12.77 score 1.5k scripts 33 dependents

bioc

MSnbase:Base Functions and Classes for Mass Spectrometry and Proteomics

MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.

Maintained by Laurent Gatto. Last updated 15 days ago.

immunooncology infrastructure proteomics massspectrometry qualitycontrol dataimport bioconductor bioinformatics mass-spectrometry proteomics-data visualisation cpp

131 stars 12.76 score 772 scripts 36 dependents

bioc

bsseq:Analyze, manage and store whole-genome methylation data

A collection of tools for analyzing and visualizing whole-genome methylation data from sequencing. This includes whole-genome bisulfite sequencing and Oxford nanopore data.

Maintained by Kasper Daniel Hansen. Last updated 3 months ago.

dnamethylation cpp

37 stars 12.26 score 676 scripts 15 dependents

andyliaw-mrk

randomForest:Breiman and Cutlers Random Forests for Classification and Regression

Classification and regression based on a forest of trees using random inputs, based on Breiman (2001) <DOI:10.1023/A:1010933404324>.

Maintained by Andy Liaw. Last updated 6 months ago.

fortran

46 stars 12.23 score 35k scripts 282 dependents

ncss-tech

aqp:Algorithms for Quantitative Pedology

The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.

Maintained by Dylan Beaudette. Last updated 1 months ago.

digital-soil-mapping ncss-tech nrcs pedology pedometrics soil soil-survey usda

55 stars 11.90 score 1.2k scripts 2 dependents

crunch-io

crunch:Crunch.io Data Tools

The Crunch.io service <https://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.

Maintained by Greg Freedman Ellis. Last updated 8 days ago.

9 stars 10.47 score 200 scripts 2 dependents

bioc

Cardinal:A mass spectrometry imaging toolbox for statistical analysis

Implements statistical & computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.

Maintained by Kylie Ariel Bemis. Last updated 3 months ago.

software infrastructure proteomics lipidomics massspectrometry imagingmassspectrometry immunooncology normalization clustering classification regression

48 stars 10.32 score 200 scripts

ropensci

jqr:Client for 'jq', a 'JSON' Processor

Client for 'jq', a 'JSON' processor (<https://jqlang.github.io/jq/>), written in C. 'jq' allows the following with 'JSON' data: index into, parse, do calculations, cut up and filter, change key names and values, perform conditionals and comparisons, and more.

Maintained by Jeroen Ooms. Last updated 4 months ago.

jq json

144 stars 10.04 score 95 scripts 28 dependents

bioc

methylumi:Handle Illumina methylation data

This package provides classes for holding and manipulating Illumina methylation data. Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. An "intelligent" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included.

Maintained by Sean Davis. Last updated 5 months ago.

dnamethylation twochannel preprocessing qualitycontrol cpgisland

9 stars 9.90 score 89 scripts 9 dependents

jeffreyevans

spatialEco:Spatial Analysis and Modelling Utilities

Utilities to support spatial data manipulation, query, sampling and modelling in ecological applications. Functions include models for species population density, spatial smoothing, multivariate separability, point process model for creating pseudo- absences and sub-sampling, Quadrant-based sampling and analysis, auto-logistic modeling, sampling models, cluster optimization, statistical exploratory tools and raster-based metrics.

Maintained by Jeffrey S. Evans. Last updated 26 days ago.

biodiversity conservation ecology r-spatial raster spatial vector

110 stars 9.55 score 736 scripts 2 dependents

usdaforestservice

gdalraster:Bindings to the 'Geospatial Data Abstraction Library' Raster API

Interface to the Raster API of the 'Geospatial Data Abstraction Library' ('GDAL', <https://gdal.org>). Bindings are implemented in an exposed C++ class encapsulating a 'GDALDataset' and its raster band objects, along with several stand-alone functions. These support manual creation of uninitialized datasets, creation from existing raster as template, read/set dataset parameters, low level I/O, color tables, raster attribute tables, virtual raster (VRT), and 'gdalwarp' wrapper for reprojection and mosaicing. Includes 'GDAL' algorithms ('dem_proc()', 'polygonize()', 'rasterize()', etc.), and functions for coordinate transformation and spatial reference systems. Calling signatures resemble the native C, C++ and Python APIs provided by the 'GDAL' project. Includes raster 'calc()' to evaluate a given R expression on a layer or stack of layers, with pixel x/y available as variables in the expression; and raster 'combine()' to identify and count unique pixel combinations across multiple input layers, with optional output of the pixel-level combination IDs. Provides raster display using base 'graphics'. Bindings to a subset of the 'OGR' API are also included for managing vector data sources. Bindings to a subset of the Virtual Systems Interface ('VSI') are also included to support operations on 'GDAL' virtual file systems. These are general utility functions that abstract file system operations on URLs, cloud storage services, 'Zip'/'GZip'/'7z'/'RAR' archives, and in-memory files. 'gdalraster' may be useful in applications that need scalable, low-level I/O, or prefer a direct 'GDAL' API.

Maintained by Chris Toney. Last updated 4 days ago.

gdal geospatial raster vector cpp

41 stars 9.52 score 32 scripts 3 dependents

bioc

matter:Out-of-core statistical computing and signal processing

Toolbox for larger-than-memory scientific computing and visualization, providing efficient out-of-core data structures using files or shared memory, for dense and sparse vectors, matrices, and arrays, with applications to nonuniformly sampled signals and images.

Maintained by Kylie A. Bemis. Last updated 4 months ago.

infrastructure datarepresentation dataimport dimensionreduction preprocessing cpp

57 stars 9.52 score 64 scripts 2 dependents

trinker

textshape:Tools for Reshaping Text

Tools that can be used to reshape and restructure text data.

Maintained by Tyler Rinker. Last updated 12 months ago.

data-reshaping manipulation sentence-boundary-detection text-data text-formating tidy

50 stars 9.18 score 266 scripts 34 dependents

flr

FLCore:Core Package of FLR, Fisheries Modelling in R

Core classes and methods for FLR, a framework for fisheries modelling and management strategy simulation in R. Developed by a team of fisheries scientists in various countries. More information can be found at <http://flr-project.org/>.

Maintained by Iago Mosqueira. Last updated 9 days ago.

fisheries flr fisheries-modelling

16 stars 8.78 score 956 scripts 23 dependents

richfitz

diversitree:Comparative 'Phylogenetic' Analyses of Diversification

Contains a number of comparative 'phylogenetic' methods, mostly focusing on analysing diversification and character evolution. Contains implementations of 'BiSSE' (Binary State 'Speciation' and Extinction) and its unresolved tree extensions, 'MuSSE' (Multiple State 'Speciation' and Extinction), 'QuaSSE', 'GeoSSE', and 'BiSSE-ness' Other included methods include Markov models of discrete and continuous trait evolution and constant rate 'speciation' and extinction.

Maintained by Richard G. FitzJohn. Last updated 6 months ago.

fftw3 gsl openblas cpp

33 stars 8.50 score 524 scripts 4 dependents

dkaschek

dMod:Dynamic Modeling and Parameter Estimation in ODE Models

The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.

Maintained by Daniel Kaschek. Last updated 23 days ago.

20 stars 8.35 score 251 scripts

ahb108

rcarbon:Calibration and Analysis of Radiocarbon Dates

Enables the calibration and analysis of radiocarbon dates, often but not exclusively for the purposes of archaeological research. It includes functions not only for basic calibration, uncalibration, and plotting of one or more dates, but also a statistical framework for building demographic and related longitudinal inferences from aggregate radiocarbon date lists, including: Monte-Carlo simulation test (Timpson et al 2014 <doi:10.1016/j.jas.2014.08.011>), random mark permutation test (Crema et al 2016 <doi:10.1371/journal.pone.0154809>) and spatial permutation tests (Crema, Bevan, and Shennan 2017 <doi:10.1016/j.jas.2017.09.007>).

Maintained by Enrico Crema. Last updated 7 months ago.

34 stars 8.14 score 274 scripts 2 dependents

bioc

beadarray:Quality assessment and low-level analysis for Illumina BeadArray data

The package is able to read bead-level data (raw TIFFs and text files) output by BeadScan as well as bead-summary data from BeadStudio. Methods for quality assessment and low-level analysis are provided.

Maintained by Mark Dunning. Last updated 5 months ago.

microarray onechannel qualitycontrol preprocessing

7.88 score 70 scripts 4 dependents

frankportman

bayesAB:Fast Bayesian Methods for AB Testing

A suite of functions that allow the user to analyze A/B test data in a Bayesian framework. Intended to be a drop-in replacement for common frequentist hypothesis test such as the t-test and chi-sq test.

Maintained by Frank Portman. Last updated 4 years ago.

ab-testing bayesian-methods bayesian-tests cpp

308 stars 7.43 score 88 scripts

momx

Momocs:Morphometrics using R

The goal of 'Momocs' is to provide a complete, convenient, reproducible and open-source toolkit for 2D morphometrics. It includes most common 2D morphometrics approaches on outlines, open outlines, configurations of landmarks, traditional morphometrics, and facilities for data preparation, manipulation and visualization with a consistent grammar throughout. It allows reproducible, complex morphometrics analyses and other morphometrics approaches should be easy to plug in, or develop from, on top of this canvas.

Maintained by Vincent Bonhomme. Last updated 1 years ago.

morphometrics

51 stars 7.42 score 346 scripts

meireles

spectrolab:Class and Methods for Spectral Data

Input/Output, processing and visualization of spectra taken with different spectrometers, including SVC (Spectra Vista), ASD and PSR (Spectral Evolution). Implements an S3 class spectra that other packages can build on. Provides methods to access, plot, manipulate, splice sensor overlap, vector normalize and smooth spectra.

Maintained by Jose Eduardo Meireles. Last updated 3 months ago.

science

16 stars 7.39 score 256 scripts

bioc

shinyMethyl:Interactive visualization for Illumina methylation arrays

Interactive tool for visualizing Illumina methylation array data. Both the 450k and EPIC array are supported.

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

dnamethylation microarray twochannel preprocessing qualitycontrol methylationarray

5 stars 7.34 score 42 scripts

flr

FLBRP:Reference Points for Fisheries Management

Calculates a range of biological reference points based upon yield per recruit and stock recruit based equilibrium calculations. These include F based reference points like F0.1, FMSY and biomass based reference points like BMSY.

Maintained by Iago Mosqueira. Last updated 4 months ago.

reference points fisheries flr cpp

2 stars 6.58 score 350 scripts 4 dependents

midasverse

rMIDAS:Multiple Imputation with Denoising Autoencoders

A tool for multiply imputing missing data using 'MIDAS', a deep learning method based on denoising autoencoder neural networks. This algorithm offers significant accuracy and efficiency advantages over other multiple imputation strategies, particularly when applied to large datasets with complex features. Alongside interfacing with 'Python' to run the core algorithm, this package contains functions for processing data before and after model training, running imputation model diagnostics, generating multiple completed datasets, and estimating regression models on these datasets.

Maintained by Thomas Robinson. Last updated 1 years ago.

deep-learning imputation-methods neural-network reticulate tensorflow

34 stars 6.53 score 33 scripts

jazznbass

scan:Single-Case Data Analyses for Single and Multiple Baseline Designs

A collection of procedures for analysing, visualising, and managing single-case data. These include piecewise linear regression models, multilevel models, overlap indices ('PND', 'PEM', 'PAND', 'PET', 'tau-u', 'baseline corrected tau', 'CDC'), and randomization tests. Data preparation functions support outlier detection, handling missing values, scaling, and custom transformations. An export function helps to generate html, word, and latex tables in a publication friendly style. More details can be found in the online book 'Analyzing single-case data with R and scan', Juergen Wilbert (2025) <https://jazznbass.github.io/scan-Book/>.

Maintained by Juergen Wilbert. Last updated 10 days ago.

4 stars 6.47 score 62 scripts 1 dependents

bioc

lumi:BeadArray Specific Methods for Illumina Methylation and Expression Microarrays

The lumi package provides an integrated solution for the Illumina microarray data analysis. It includes functions of Illumina BeadStudio (GenomeStudio) data input, quality control, BeadArray-specific variance stabilization, normalization and gene annotation at the probe level. It also includes the functions of processing Illumina methylation microarrays, especially Illumina Infinium methylation microarrays.

Maintained by Lei Huang. Last updated 5 months ago.

microarray onechannel preprocessing dnamethylation qualitycontrol twochannel

6.26 score 294 scripts 5 dependents

highlanderlab

SIMplyBee:'AlphaSimR' Extension for Simulating Honeybee Populations and Breeding Programmes

An extension of the 'AlphaSimR' package (<https://cran.r-project.org/package=AlphaSimR>) for stochastic simulations of honeybee populations and breeding programmes. 'SIMplyBee' enables simulation of individual bees that form a colony, which includes a queen, fathers (drones the queen mated with), virgin queens, workers, and drones. Multiple colony can be merged into a population of colonies, such as an apiary or a whole country of colonies. Functions enable operations on castes, colony, or colonies, to ease 'R' scripting of whole populations. All 'AlphaSimR' functionality with respect to genomes and genetic and phenotype values is available and further extended for honeybees, including haplo-diploidy, complementary sex determiner locus, colony events (swarming, supersedure, etc.), and colony phenotype values.

Maintained by Jana Obšteter. Last updated 6 months ago.

cpp openmp

2 stars 6.24 score 18 scripts

mingdeyu

dgpsi:Interface to 'dgpsi' for Deep and Linked Gaussian Process Emulations

Interface to the 'python' package 'dgpsi' for Gaussian process, deep Gaussian process, and linked deep Gaussian process emulations of computer models and networks using stochastic imputation (SI). The implementations follow Ming & Guillas (2021) <doi:10.1137/20M1323771> and Ming, Williamson, & Guillas (2023) <doi:10.1080/00401706.2022.2124311> and Ming & Williamson (2023) <doi:10.48550/arXiv.2306.01212>. To get started with the package, see <https://mingdeyu.github.io/dgpsi-R/>.

Maintained by Deyu Ming. Last updated 4 days ago.

deep-gaussian-processes emulation gaussian-processes surrogate-models

6.03 score 76 scripts

bioc

globaltest:Testing Groups of Covariates/Features for Association with a Response Variable, with Applications to Gene Set Testing

The global test tests groups of covariates (or features) for association with a response variable. This package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.

Maintained by Jelle Goeman. Last updated 5 months ago.

microarray onechannel bioinformatics differentialexpression go pathways

5.89 score 79 scripts 6 dependents

bioc

sparrow:Take command of set enrichment analyses through a unified interface

Provides a unified interface to a variety of GSEA techniques from different bioconductor packages. Results are harmonized into a single object and can be interrogated uniformly for quick exploration and interpretation of results. Interactive exploration of GSEA results is enabled through a shiny app provided by a sparrow.shiny sibling package.

Maintained by Steve Lianoglou. Last updated 12 days ago.

genesetenrichment pathways bioinformatics gsea

21 stars 5.74 score 13 scripts

pvermees

provenance:Statistical Toolbox for Sedimentary Provenance Analysis

Bundles a number of established statistical methods to facilitate the visual interpretation of large datasets in sedimentary geology. Includes functionality for adaptive kernel density estimation, principal component analysis, correspondence analysis, multidimensional scaling, generalised procrustes analysis and individual differences scaling using a variety of dissimilarity measures. Univariate provenance proxies, such as single-grain ages or (isotopic) compositions are compared with the Kolmogorov-Smirnov, Kuiper, Wasserstein-2 or Sircombe-Hazelton L2 distances. Categorical provenance proxies such as chemical compositions are compared with the Aitchison and Bray-Curtis distances,and count data with the chi-square distance. Varietal data can either be converted to one or more distributional datasets, or directly compared using the multivariate Wasserstein distance. Also included are tools to plot compositional and count data on ternary diagrams and point-counting data on radial plots, to calculate the sample size required for specified levels of statistical precision, and to assess the effects of hydraulic sorting on detrital compositions. Includes an intuitive query-based user interface for users who are not proficient in R.

Maintained by Pieter Vermeesch. Last updated 3 months ago.

14 stars 5.52 score 79 scripts 1 dependents

openanalytics

inTextSummaryTable:Creation of in-Text Summary Table

Creation of tables of summary statistics or counts for clinical data (for 'TLFs'). These tables can be exported as in-text table (with the 'flextable' package) for a Clinical Study Report (Word format) or a 'topline' presentation (PowerPoint format), or as interactive table (with the 'DT' package) to an html document for clinical data review.

Maintained by Laure Cougnaud. Last updated 10 months ago.

1 stars 5.52 score 47 scripts

eglenn

acs:Download, Manipulate, and Present American Community Survey and Decennial Data from the US Census

Provides a general toolkit for downloading, managing, analyzing, and presenting data from the U.S. Census (<https://www.census.gov/data/developers/data-sets.html>), including SF1 (Decennial short-form), SF3 (Decennial long-form), and the American Community Survey (ACS). Confidence intervals provided with ACS data are converted to standard errors to be bundled with estimates in complex acs objects. Package provides new methods to conduct standard operations on acs objects and present/plot data in statistically appropriate ways.

Maintained by Ezra Haber Glenn. Last updated 6 years ago.

11 stars 5.33 score 430 scripts 3 dependents

bioc

topdownr:Investigation of Fragmentation Conditions in Top-Down Proteomics

The topdownr package allows automatic and systemic investigation of fragment conditions. It creates Thermo Orbitrap Fusion Lumos method files to test hundreds of fragmentation conditions. Additionally it provides functions to analyse and process the generated MS data and determine the best conditions to maximise overall fragment coverage.

Maintained by Sebastian Gibb. Last updated 5 months ago.

immunooncology infrastructure proteomics massspectrometry coverage mass-spectrometry topdown

1 stars 5.08 score

simonyansenzhao

wsrf:Weighted Subspace Random Forest for Classification

A parallel implementation of Weighted Subspace Random Forest. The Weighted Subspace Random Forest algorithm was proposed in the International Journal of Data Warehousing and Mining by Baoxun Xu, Joshua Zhexue Huang, Graham Williams, Qiang Wang, and Yunming Ye (2012) <DOI:10.4018/jdwm.2012040103>. The algorithm can classify very high-dimensional data with random forests built using small subspaces. A novel variable weighting method is used for variable subspace selection in place of the traditional random variable sampling.This new approach is particularly useful in building models from high-dimensional data.

Maintained by He Zhao. Last updated 2 years ago.

cpp

14 stars 4.89 score 11 scripts

quadrama

DramaAnalysis:Analysis of Dramatic Texts

Analysis of preprocessed dramatic texts, with respect to literary research. The package provides functions to analyze and visualize information about characters, stage directions, the dramatic structure and the text itself. The dramatic texts are expected to be in CSV format, which can be installed from within the package, sample texts are provided. The package and the reasoning behind it are described in Reiter et al. (2017) <doi:10.18420/in2017_119>.

Maintained by Nils Reiter. Last updated 5 years ago.

corpus-linguistics digital-humanities drama dramatic-texts statistics

15 stars 4.79 score 41 scripts

bioc

BiSeq:Processing and analyzing bisulfite sequencing data

The BiSeq package provides useful classes and functions to handle and analyze targeted bisulfite sequencing (BS) data such as reduced-representation bisulfite sequencing (RRBS) data. In particular, it implements an algorithm to detect differentially methylated regions (DMRs). The package takes already aligned BS data from one or multiple samples.

Maintained by Katja Hebestreit. Last updated 5 months ago.

genetics sequencing methylseq dnamethylation

4.78 score 30 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.

immunooncology metabolomics massspectrometry network regression

4.70 score 1 scripts

hubverse-org

hubValidations:Testing framework for hubverse hub validations

This package aims at providing a simple interface to run validations on data and metadata submitted to a hubverse modeling hub. Validation tests can be run at different levels (single file, single folder, whole repository) and locally as well as part of a continuous integration workflow.

Maintained by Anna Krystalli. Last updated 17 days ago.

hubverse

1 stars 4.67 score 27 scripts 1 dependents

richfitz

TRAMPR:'TRFLP' Analysis and Matching Package for R

Matching terminal restriction fragment length polymorphism ('TRFLP') profiles between unknown samples and a database of known samples. 'TRAMPR' facilitates analysis of many unknown profiles at once, and provides tools for working directly with electrophoresis output through to generating summaries suitable for community analyses with R's rich set of statistical functions. 'TRAMPR' also resolves the issues of multiple 'TRFLP' profiles within a species, and shared 'TRFLP' profiles across species.

Maintained by Rich FitzJohn. Last updated 3 years ago.

4.66 score 23 scripts

bioc

MethylAid:Visual and interactive quality control of large Illumina DNA Methylation array data sets

A visual and interactive web application using RStudio's shiny package. Bad quality samples are detected using sample-dependent and sample-independent controls present on the array and user adjustable thresholds. In depth exploration of bad quality samples can be performed using several interactive diagnostic plots of the quality control probes present on the array. Furthermore, the impact of any batch effect provided by the user can be explored.

Maintained by L.J.Sinke. Last updated 5 months ago.

dnamethylation methylationarray microarray twochannel qualitycontrol batcheffect visualization gui

4.51 score 16 scripts

bioc

INSPEcT:Modeling RNA synthesis, processing and degradation with RNA-seq data

INSPEcT (INference of Synthesis, Processing and dEgradation rates from Transcriptomic data) RNA-seq data in time-course experiments or steady-state conditions, with or without the support of nascent RNA data.

Maintained by Stefano de Pretis. Last updated 5 months ago.

sequencing rnaseq generegulation timecourse systemsbiology

4.38 score 9 scripts

bioc

MassArray:Analytical Tools for MassArray Data

This package is designed for the import, quality control, analysis, and visualization of methylation data generated using Sequenom's MassArray platform. The tools herein contain a highly detailed amplicon prediction for optimal assay design. Also included are quality control measures of data, such as primer dimer and bisulfite conversion efficiency estimation. Methylation data are calculated using the same algorithms contained in the EpiTyper software package. Additionally, automatic SNP-detection can be used to flag potentially confounded data from specific CG sites. Visualization includes barplots of methylation data as well as UCSC Genome Browser-compatible BED tracks. Multiple assays can be positionally combined for integrated analysis.

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

immunooncology dnamethylation snp massspectrometry genetics dataimport visualization

4.30 score 1 scripts

bioc

mogsa:Multiple omics data integrative clustering and gene set analysis

This package provide a method for doing gene set analysis based on multiple omics data.

Maintained by Chen Meng. Last updated 5 months ago.

geneexpression principalcomponent statisticalmethod clustering software

4.29 score 49 scripts

trackage

tripEstimation:Metropolis Sampler and Supporting Functions for Estimating Animal Movement from Archival Tags and Satellite Fixes

Data handling and estimation functions for animal movement estimation from archival or satellite tags. Helper functions are included for making image summaries binned by time interval from Markov Chain Monte Carlo simulations.

Maintained by Michael D. Sumner. Last updated 2 years ago.

4 stars 4.19 score 13 scripts

softwaredeng

RRF:Regularized Random Forest

Feature Selection with Regularized Random Forest. This package is based on the 'randomForest' package by Andy Liaw. The key difference is the RRF() function that builds a regularized random forest. Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener, Regularized random forest for classification by Houtao Deng, Regularized random forest for regression by Xin Guan. Reference: Houtao Deng (2013) <doi:10.48550/arXiv.1306.0237>.

Maintained by Houtao Deng. Last updated 5 months ago.

fortran

3.81 score 118 scripts 3 dependents

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.

differentialmethylation sequencing hiddenmarkovmodel coverage

3.78 score 3 scripts

bioc

DMCFB:Differentially Methylated Cytosines via a Bayesian Functional Approach

DMCFB is a pipeline for identifying differentially methylated cytosines using a Bayesian functional regression model in bisulfite sequencing data. By using a functional regression data model, it tries to capture position-specific, group-specific and other covariates-specific methylation patterns as well as spatial correlation patterns and unknown underlying models of methylation data. It is robust and flexible with respect to the true underlying models and inclusion of any covariates, and the missing values are imputed using spatial correlation between positions and samples. A Bayesian approach is adopted for estimation and inference in the proposed method.

Maintained by Farhad Shokoohi. Last updated 5 months ago.

differentialmethylation sequencing coverage bayesian regression

3.60 score 3 scripts

inbo

n2kanalysis:Generic Functions to Analyse Data from the 'Natura 2000' Monitoring

All generic functions and classes for the analysis for the 'Natura 2000' monitoring. The classes contain all required data and definitions to fit the model without the need to access other sources. Potentially they might need access to one or more parent objects. An aggregation object might for example need the result of an imputation object. The actual definition of the analysis, using these generic function and classes, is defined in dedictated analysis R packages for every monitoring scheme. For example 'abvanalysis' and 'watervogelanalysis'.

Maintained by Thierry Onkelinx. Last updated 2 months ago.

analysis monitoring natura2000

1 stars 3.18 score 7 scripts

tdhock

inlinedocs:Convert Inline Comments to Documentation

Generates Rd files from R source code with comments. The main features of the default syntax are that (1) docs are defined in comments near the relevant code, (2) function argument names are not repeated in comments, and (3) examples are defined in R code, not comments. It is also easy to define a new syntax.

Maintained by Toby Dylan Hocking. Last updated 1 years ago.

2 stars 3.14 score 47 scripts

alidalba

mazeinda:Monotonic Association on Zero-Inflated Data

Methods for calculating and testing the significance of pairwise monotonic association from and based on the work of Pimentel (2009) <doi:10.4135/9781412985291.n2>. Computation of association of vectors from one or multiple sets can be performed in parallel thanks to the packages 'foreach' and 'doMC'.

Maintained by Alice Albasi. Last updated 3 years ago.

2.70 score 10 scripts

cran

adimpro:Adaptive Smoothing of Digital Images

Implements tools for manipulation of digital images and the Propagation Separation approach by Polzehl and Spokoiny (2006) <DOI:10.1007/s00440-005-0464-1> for smoothing digital images, see Polzehl and Tabelow (2007) <DOI:10.18637/jss.v019.i01>.

Maintained by Karsten Tabelow. Last updated 6 months ago.

fortran openblas openmp

2.08 score 2 dependents

cran

jointest:Multivariate Testing Through Joint Resampling-Based Tests

Runs resampling-based tests jointly, e.g., sign-flip score tests from Hemerik et al., (2020) <doi:10.1111/rssb.12369>, to allow for multivariate testing, i.e., weak and strong control of the Familywise Error Rate or True Discovery Proportion.

Maintained by Livio Finos. Last updated 3 months ago.

2.00 score

cran

onlineBcp:Online Bayesian Methods for Change Point Analysis

It implements the online Bayesian methods for change point analysis. It can also perform missing data imputation with methods from 'VIM'. The reference is Yigiter A, Chen J, An L, Danacioglu N (2015) <doi:10.1080/02664763.2014.1001330>. The link to the package is <https://CRAN.R-project.org/package=onlineBcp>.

Maintained by Hongyan Xu. Last updated 3 years ago.

1 stars 2.00 score

cran

ensembleBMA:Probabilistic Forecasting using Ensembles and Bayesian Model Averaging

Bayesian Model Averaging to create probabilistic forecasts from ensemble forecasts and weather observations <https://stat.uw.edu/sites/default/files/files/reports/2007/tr516.pdf>.

Maintained by Chris Fraley. Last updated 3 years ago.

3 stars 1.95 score 1 dependents

cran

SeaVal:Validation of Seasonal Weather Forecasts

Provides tools for processing and evaluating seasonal weather forecasts, with an emphasis on tercile forecasts. We follow the World Meteorological Organization's "Guidance on Verification of Operational Seasonal Climate Forecasts", S.J.Mason (2018, ISBN: 978-92-63-11220-0, URL: <https://library.wmo.int/idurl/4/56227>). The development was supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 869730 (CONFER). A comprehensive online tutorial is available at <https://seasonalforecastingengine.github.io/SeaValDoc/>.

Maintained by Claudio Heinrich-Mertsching. Last updated 10 months ago.

1.70 score

tkhamiak

superbiclust:Generating Robust Biclusters from a Bicluster Set (Ensemble Biclustering)

Biclusters are submatrices in the data matrix which satisfy certain conditions of homogeneity. Package contains functions for generating robust biclusters with respect to the initialization parameters for a given bicluster solution contained in a bicluster set in data, the procedure is also known as ensemble biclustering. The set of biclusters is evaluated based on the similarity of its elements (the overlap), and afterwards the hierarchical tree is constructed to obtain cut-off points for the classes of robust biclusters. The result is a number of robust (or super) biclusters with none or low overlap.

Maintained by Tatsiana Khamiakova. Last updated 4 years ago.

1.48 score 2 scripts 1 dependents

cran

SCMA:Single-Case Meta-Analysis

Perform meta-analysis of single-case experiments, including calculating various effect size measures (SMD, PND, PEM and NAP) and probability combining (additive and multiplicative method), as discussed in Bulte and Onghena (2013) <doi:10.22237/jmasm/1383280020>.

Maintained by Tamal Kumar De. Last updated 5 years ago.

1.00 score