R-universe search: needs:tidyselect

tidyverse

dplyr:A Grammar of Data Manipulation

A fast, consistent tool for working with data frame like objects, both in memory and out of memory.

Maintained by Hadley Wickham. Last updated 28 days ago.

data-manipulation grammar cpp

4.8k stars 24.68 score 659k scripts 7.8k dependents

tidyverse

tidyr:Tidy Messy Data

Tools to help to create tidy data, where each column is a variable, each row is an observation, and each cell contains a single value. 'tidyr' contains tools for changing the shape (pivoting) and hierarchy (nesting and 'unnesting') of a dataset, turning deeply nested lists into rectangular data frames ('rectangling'), and extracting values out of string columns. It also includes tools for working with missing values (both implicit and explicit).

Maintained by Hadley Wickham. Last updated 28 days ago.

tidy-data cpp

1.4k stars 22.88 score 168k scripts 5.5k dependents

tidymodels

broom:Convert Statistical Objects into Tidy Tibbles

Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.

Maintained by Simon Couch. Last updated 3 days ago.

modeling tidy-data

1.5k stars 21.58 score 37k scripts 1.5k dependents

tidyverse

tidyverse:Easily Install and Load the 'Tidyverse'

The 'tidyverse' is a set of packages that work in harmony because they share common data representations and 'API' design. This package is designed to make it easy to install and load multiple 'tidyverse' packages in a single step. Learn more about the 'tidyverse' at <https://www.tidyverse.org>.

Maintained by Hadley Wickham. Last updated 5 months ago.

data-science tidyverse

1.7k stars 20.23 score 664k scripts 125 dependents

tidyverse

readr:Read Rectangular Text Data

The goal of 'readr' is to provide a fast and friendly way to read rectangular data (like 'csv', 'tsv', and 'fwf'). It is designed to flexibly parse many types of data found in the wild, while still cleanly failing when data unexpectedly changes.

Maintained by Jennifer Bryan. Last updated 8 months ago.

csv fwf parsing cpp

1.0k stars 20.06 score 132k scripts 2.1k dependents

tidyverse

dbplyr:A 'dplyr' Back End for Databases

A 'dplyr' back end for databases that allows you to work with remote database tables as if they are in-memory data frames. Basic features works with any database that has a 'DBI' back end; more advanced features require 'SQL' translation to be provided by the package author.

Maintained by Hadley Wickham. Last updated 4 months ago.

database

481 stars 19.72 score 5.2k scripts 736 dependents

plotly

plotly:Create Interactive Web Graphics via 'plotly.js'

Create interactive web graphics from 'ggplot2' graphs and/or a custom interface to the (MIT-licensed) JavaScript library 'plotly.js' inspired by the grammar of graphics.

Maintained by Carson Sievert. Last updated 4 months ago.

d3js data-visualization ggplot2 javascript plotly shiny webgl

2.6k stars 19.43 score 93k scripts 797 dependents

sfirke

janitor:Simple Tools for Examining and Cleaning Dirty Data

The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and explore duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness.

Maintained by Sam Firke. Last updated 3 months ago.

data-analysis data-cleaning data-science dirty-data excel pivot-tables spss tabulations tidyverse

1.4k stars 19.40 score 35k scripts 231 dependents

apache

arrow:Integration to 'Apache' 'Arrow'

'Apache' 'Arrow' <https://arrow.apache.org/> is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. This package provides an interface to the 'Arrow C++' library.

Maintained by Jonathan Keane. Last updated 2 months ago.

arrow curl openssl cpp

15k stars 19.25 score 10k scripts 82 dependents

topepo

caret:Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Maintained by Max Kuhn. Last updated 4 months ago.

1.6k stars 19.24 score 61k scripts 303 dependents

tidymodels

recipes:Preprocessing and Feature Engineering Steps for Modeling

A recipe prepares your data for modeling. We provide an extensible framework for pipeable sequences of feature engineering steps provides preprocessing tools to be applied to data. Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting processed output can then be used as inputs for statistical or machine learning models.

Maintained by Max Kuhn. Last updated 3 days ago.

586 stars 18.80 score 7.2k scripts 383 dependents

tidyverse

haven:Import and Export 'SPSS', 'Stata' and 'SAS' Files

Import foreign statistical formats into R via the embedded 'ReadStat' C library, <https://github.com/WizardMac/ReadStat>.

Maintained by Hadley Wickham. Last updated 6 months ago.

sas spss stata zlib cpp

427 stars 18.63 score 18k scripts 682 dependents

rstudio

gt:Easily Create Presentation-Ready Display Tables

Build display tables from tabular data with an easy-to-use set of functions. With its progressive approach, we can construct display tables with a cohesive set of table parts. Table values can be formatted using any of the included formatting functions. Footnotes and cell styles can be precisely added through a location targeting system. The way in which 'gt' handles things for you means that you don't often have to worry about the fine details.

Maintained by Richard Iannone. Last updated 26 days ago.

docx easy-to-use html latex rtf summary-tables

2.1k stars 18.36 score 20k scripts 112 dependents

tidyverse

vroom:Read and Write Rectangular Text Data Quickly

The goal of 'vroom' is to read and write data (like 'csv', 'tsv' and 'fwf') quickly. When reading it uses a quick initial indexing step, then reads the values lazily , so only the data you actually use needs to be read. The writer formats the data in parallel and writes to disk asynchronously from formatting.

Maintained by Jennifer Bryan. Last updated 7 months ago.

csv csv-parser fixed-width-text tsv tsv-parser cpp

625 stars 17.82 score 4.5k scripts 2.1k dependents

gesistsa

rio:A Swiss-Army Knife for Data I/O

Streamlined data import and export by making assumptions that the user is probably willing to make: 'import()' and 'export()' determine the data format from the file extension, reasonable defaults are used for data import and export, web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly, and fast import packages are used where appropriate. An additional convenience function, 'convert()', provides a simple method for converting between file types.

Maintained by Chung-hong Chan. Last updated 3 months ago.

csv csvy data data-science excel io rio sas spss stata

610 stars 17.10 score 7.8k scripts 74 dependents

bioc

clusterProfiler:A universal enrichment tool for interpreting omics data

This package supports functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation. It provides a univeral interface for gene functional annotation from a variety of sources and thus can be applied in diverse scenarios. It provides a tidy interface to access, manipulate, and visualize enrichment results to help users achieve efficient data interpretation. Datasets obtained from multiple treatments and time points can be analyzed and compared in a single run, easily revealing functional consensus and differences among distinct conditions.

Maintained by Guangchuang Yu. Last updated 4 months ago.

annotation clustering genesetenrichment go kegg multiplecomparison pathways reactome visualization enrichment-analysis gsea

1.1k stars 17.03 score 11k scripts 48 dependents

ddsjoberg

gtsummary:Presentation-Ready Data Summary and Analytic Result Tables

Creates presentation-ready tables summarizing data sets, regression models, and more. The code to create the tables is concise and highly customizable. Data frames can be summarized with any function, e.g. mean(), median(), even user-written functions. Regression models are summarized and include the reference rows for categorical variables. Common regression models, such as logistic regression and Cox proportional hazards regression, are automatically identified and the tables are pre-filled with appropriate column headers.

Maintained by Daniel D. Sjoberg. Last updated 6 days ago.

easy-to-use gt html5 regression-models reproducibility reproducible-research statistics summary-statistics summary-tables table1 tableone

1.1k stars 17.02 score 8.2k scripts 15 dependents

thomasp85

ggraph:An Implementation of Grammar of Graphics for Graphs and Networks

The grammar of graphics as implemented in ggplot2 is a poor fit for graph and network visualizations due to its reliance on tabular data input. ggraph is an extension of the ggplot2 API tailored to graph visualizations and provides the same flexible approach to building up plots layer by layer.

Maintained by Thomas Lin Pedersen. Last updated 1 years ago.

ggplot-extension ggplot2 graph-visualization network-visualization visualization cpp

1.1k stars 16.96 score 9.2k scripts 111 dependents

satijalab

Seurat:Tools for Single Cell Genomics

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.

Maintained by Paul Hoffman. Last updated 1 years ago.

human-cell-atlas single-cell-genomics single-cell-rna-seq cpp

2.4k stars 16.86 score 50k scripts 73 dependents

juliasilge

tidytext:Text Mining using 'dplyr', 'ggplot2', and Other Tidy Tools

Using tidy data principles can make many text mining tasks easier, more effective, and consistent with tools already in wide use. Much of the infrastructure needed for text mining with tidy data frames already exists in packages like 'dplyr', 'broom', 'tidyr', and 'ggplot2'. In this package, we provide functions and supporting data sets to allow conversion of text to and from tidy formats, and to switch seamlessly between tidy tools and existing text mining packages.

Maintained by Julia Silge. Last updated 12 months ago.

natural-language-processing text-mining tidy-data tidyverse

1.2k stars 16.86 score 17k scripts 61 dependents

bioc

ggtree:an R package for visualization of tree and annotation data

'ggtree' extends the 'ggplot2' plotting system which implemented the grammar of graphics. 'ggtree' is designed for visualization and annotation of phylogenetic trees and other tree-like structures with their annotation data.

Maintained by Guangchuang Yu. Last updated 5 months ago.

alignment annotation clustering dataimport multiplesequencealignment phylogenetics reproducibleresearch software visualization annotations ggplot2 phylogenetic-trees

871 stars 16.83 score 5.1k scripts 109 dependents

ropensci

skimr:Compact and Flexible Summaries of Data

A simple to use summary function that can be used with pipes and displays nicely in the console. The default summary statistics may be modified by the user as can the default formatting. Support for data frames and vectors is included, and users can implement their own skim methods for specific object types as described in a vignette. Default summaries include support for inline spark graphs. Instructions for managing these on specific operating systems are given in the "Using skimr" vignette and the README.

Maintained by Elin Waring. Last updated 2 months ago.

peer-reviewed ropensci summary-statistics unconf unconf17

1.1k stars 16.80 score 18k scripts 14 dependents

andrisignorell

DescTools:Tools for Descriptive Statistics

A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.

Maintained by Andri Signorell. Last updated 3 days ago.

fortran cpp

86 stars 16.73 score 7.7k scripts 101 dependents

tidymodels

rsample:General Resampling Infrastructure

Classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).

Maintained by Hannah Frick. Last updated 20 days ago.

341 stars 16.72 score 5.2k scripts 79 dependents

stan-dev

bayesplot:Plotting for Bayesian Models

Plotting functions for posterior analysis, MCMC diagnostics, prior and posterior predictive checks, and other visualizations to support the applied Bayesian workflow advocated in Gabry, Simpson, Vehtari, Betancourt, and Gelman (2019) <doi:10.1111/rssa.12378>. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with 'Stan'.

Maintained by Jonah Gabry. Last updated 2 months ago.

bayesian ggplot2 mcmc pandoc stan statistical-graphics visualization

436 stars 16.69 score 6.5k scripts 98 dependents

kassambara

ggpubr:'ggplot2' Based Publication Ready Plots

The 'ggplot2' package is excellent and flexible for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots.

Maintained by Alboukadel Kassambara. Last updated 2 years ago.

1.2k stars 16.68 score 65k scripts 409 dependents

paul-buerkner

brms:Bayesian Regression Models using 'Stan'

Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include both theory-driven and data-driven non-linear terms, auto-correlation structures, censoring and truncation, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their prior knowledge. Models can easily be evaluated and compared using several methods assessing posterior or prior predictions. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Bürkner (2018) <doi:10.32614/RJ-2018-017>; Bürkner (2021) <doi:10.18637/jss.v100.i05>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.

Maintained by Paul-Christian Bürkner. Last updated 1 hours ago.

bayesian-inference brms multilevel-models stan statistical-models

1.3k stars 16.64 score 13k scripts 35 dependents

amices

mice:Multivariate Imputation by Chained Equations

Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.

Maintained by Stef van Buuren. Last updated 3 days ago.

chained-equations fcs imputation mice missing-data missing-values multiple-imputation multivariate-data cpp

462 stars 16.64 score 10k scripts 154 dependents

tidymodels

tidymodels:Easily Install and Load the 'Tidymodels' Packages

The tidy modeling "verse" is a collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.

Maintained by Max Kuhn. Last updated 1 months ago.

783 stars 16.52 score 66k scripts 15 dependents

tidyverse

modelr:Modelling Functions that Work with the Pipe

Functions for modelling that help you seamlessly integrate modelling into a pipeline of data manipulation and visualisation.

Maintained by Hadley Wickham. Last updated 1 years ago.

modelling

400 stars 16.46 score 6.9k scripts 1.1k dependents

tidymodels

parsnip:A Common API to Modeling and Analysis Functions

A common interface is provided to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. 'R', 'Spark', 'Stan', 'H2O', etc).

Maintained by Max Kuhn. Last updated 19 days ago.

612 stars 16.37 score 3.4k scripts 69 dependents

ggobi

GGally:Extension to 'ggplot2'

The R package 'ggplot2' is a plotting system based on the grammar of graphics. 'GGally' extends 'ggplot2' by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.

Maintained by Barret Schloerke. Last updated 11 months ago.

597 stars 16.15 score 17k scripts 154 dependents

tidyverse

dtplyr:Data Table Back-End for 'dplyr'

Provides a data.table backend for 'dplyr'. The goal of 'dtplyr' is to allow you to write 'dplyr' code that is automatically translated to the equivalent, but usually much faster, data.table code.

Maintained by Hadley Wickham. Last updated 2 months ago.

datatable dplyr

671 stars 16.11 score 2.5k scripts 148 dependents

bioc

biomaRt:Interface to BioMart databases (i.e. Ensembl)

In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis. biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite (<http://www.biomart.org>). The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. The most prominent examples of BioMart databases are maintain by Ensembl, which provides biomaRt users direct access to a diverse set of data and enables a wide range of powerful online queries from gene annotation to database mining.

Maintained by Mike Smith. Last updated 17 days ago.

annotation bioconductor biomart ensembl

38 stars 15.99 score 13k scripts 230 dependents

thomasp85

ggforce:Accelerating 'ggplot2'

The aim of 'ggplot2' is to aid in visual data investigations. This focus has led to a lack of facilities for composing specialised plots. 'ggforce' aims to be a collection of mainly new stats and geoms that fills this gap. All additional functionality is aimed to come through the official extension system so using 'ggforce' should be a stable experience.

Maintained by Thomas Lin Pedersen. Last updated 6 days ago.

ggplot-extension ggplot2 visualization cpp

929 stars 15.98 score 9.3k scripts 298 dependents

kassambara

survminer:Drawing Survival Curves using 'ggplot2'

Contains the function 'ggsurvplot()' for drawing easily beautiful and 'ready-to-publish' survival curves with the 'number at risk' table and 'censoring count plot'. Other functions are also available to plot adjusted curves for `Cox` model and to visually examine 'Cox' model assumptions.

Maintained by Alboukadel Kassambara. Last updated 5 months ago.

524 stars 15.87 score 7.0k scripts 55 dependents

tidymodels

infer:Tidy Statistical Inference

The objective of this package is to perform inference using an expressive statistical grammar that coheres with the tidy design framework.

Maintained by Simon Couch. Last updated 6 months ago.

736 stars 15.75 score 3.5k scripts 18 dependents

bioc

enrichplot:Visualization of Functional Enrichment Result

The 'enrichplot' package implements several visualization methods for interpreting functional enrichment results obtained from ORA or GSEA analysis. It is mainly designed to work with the 'clusterProfiler' package suite. All the visualization methods are developed based on 'ggplot2' graphics.

Maintained by Guangchuang Yu. Last updated 3 months ago.

annotation genesetenrichment go kegg pathways software visualization enrichment-analysis pathway-analysis

239 stars 15.71 score 3.1k scripts 58 dependents

stan-dev

rstanarm:Bayesian Applied Regression Modeling via Stan

Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.

Maintained by Ben Goodrich. Last updated 12 days ago.

bayesian bayesian-data-analysis bayesian-inference bayesian-methods bayesian-statistics multilevel-models rstan rstanarm stan statistical-modeling cpp

393 stars 15.70 score 5.0k scripts 13 dependents

njtierney

naniar:Data Structures, Summaries, and Visualisations for Missing Data

Missing values are ubiquitous in data and need to be explored and handled in the initial stages of analysis. 'naniar' provides data structures and functions that facilitate the plotting of missing values and examination of imputations. This allows missing data dependencies to be explored with minimal deviation from the common work patterns of 'ggplot2' and tidy data. The work is fully discussed at Tierney & Cook (2023) <doi:10.18637/jss.v105.i07>.

Maintained by Nicholas Tierney. Last updated 18 days ago.

data-visualisation ggplot2 missing-data missingness tidy-data

657 stars 15.63 score 5.1k scripts 9 dependents

facebook

prophet:Automatic Forecasting Procedure

Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.

Maintained by Sean Taylor. Last updated 5 months ago.

forecasting python cpp

19k stars 15.59 score 976 scripts 13 dependents

rstudio

tensorflow:R Interface to 'TensorFlow'

Interface to 'TensorFlow' <https://www.tensorflow.org/>, an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more 'CPUs' or 'GPUs' in a desktop, server, or mobile device with a single 'API'. 'TensorFlow' was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

Maintained by Tomasz Kalinowski. Last updated 5 days ago.

1.3k stars 15.47 score 3.2k scripts 75 dependents

tidymodels

yardstick:Tidy Characterizations of Model Performance

Tidy tools for quantifying how well model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).

Maintained by Emil Hvitfeldt. Last updated 19 days ago.

387 stars 15.47 score 2.2k scripts 60 dependents

r-forge

car:Companion to Applied Regression

Functions to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage, 2019.

Maintained by John Fox. Last updated 5 months ago.

15.38 score 43k scripts 919 dependents

rich-iannone

DiagrammeR:Graph/Network Visualization

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

Maintained by Richard Iannone. Last updated 2 months ago.

graph graph-functions network-graph property-graph visualization

1.7k stars 15.29 score 3.8k scripts 86 dependents

kassambara

rstatix:Pipe-Friendly Framework for Basic Statistical Tests

Provides a simple and intuitive pipe-friendly framework, coherent with the 'tidyverse' design philosophy, for performing basic statistical tests, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses. The output of each test is automatically transformed into a tidy data frame to facilitate visualization. Additional functions are available for reshaping, reordering, manipulating and visualizing correlation matrix. Functions are also included to facilitate the analysis of factorial experiments, including purely 'within-Ss' designs (repeated measures), purely 'between-Ss' designs, and mixed 'within-and-between-Ss' designs. It's also possible to compute several effect size metrics, including "eta squared" for ANOVA, "Cohen's d" for t-test and 'Cramer V' for the association between categorical variables. The package contains helper functions for identifying univariate and multivariate outliers, assessing normality and homogeneity of variances.

Maintained by Alboukadel Kassambara. Last updated 2 years ago.

458 stars 15.27 score 11k scripts 432 dependents

bbolker

broom.mixed:Tidying Methods for Mixed Models

Convert fitted objects from various R mixed-model packages into tidy data frames along the lines of the 'broom' package. The package provides three S3 generics for each model: tidy(), which summarizes a model's statistical findings such as coefficients of a regression; augment(), which adds columns to the original data such as predictions, residuals and cluster assignments; and glance(), which provides a one-row summary of model-level statistics.

Maintained by Ben Bolker. Last updated 8 days ago.

230 stars 15.22 score 4.0k scripts 37 dependents

sparklyr

sparklyr:R Interface to Apache Spark

R interface to Apache Spark, a fast and general engine for big data processing, see <https://spark.apache.org/>. This package supports connecting to local and remote Apache Spark clusters, provides a 'dplyr' compatible back-end, and provides an interface to Spark's built-in machine learning algorithms.

Maintained by Edgar Ruiz. Last updated 13 days ago.

apache-spark distributed dplyr ide livy machine-learning remote-clusters spark sparklyr

959 stars 15.20 score 4.0k scripts 21 dependents

ropensci

targets:Dynamic Function-Oriented 'Make'-Like Declarative Pipelines

Pipeline tools coordinate the pieces of computationally demanding analysis projects. The 'targets' package is a 'Make'-like pipeline tool for statistics and data science in R. The package skips costly runtime for tasks that are already up to date, orchestrates the necessary computation with implicit parallel computing, and abstracts files as R objects. If all the current output matches the current upstream code and data, then the whole pipeline is up to date, and the results are more trustworthy than otherwise. The methodology in this package borrows from GNU 'Make' (2015, ISBN:978-9881443519) and 'drake' (2018, <doi:10.21105/joss.00550>).

Maintained by William Michael Landau. Last updated 1 hours ago.

data-science high-performance-computing make peer-reviewed pipeline r-targetopia reproducibility reproducible-research targets workflow

979 stars 15.16 score 4.6k scripts 22 dependents

larmarange

labelled:Manipulating Labelled Data

Work with labelled data imported from 'SPSS' or 'Stata' with 'haven' or 'foreign'. This package provides useful functions to deal with "haven_labelled" and "haven_labelled_spss" classes introduced by 'haven' package.

Maintained by Joseph Larmarange. Last updated 1 months ago.

haven labels metadata sas spss stata

76 stars 15.04 score 2.4k scripts 98 dependents

hojsgaard

doBy:Groupwise Statistics, LSmeans, Linear Estimates, Utilities

Utility package containing: 1) Facilities for working with grouped data: 'do' something to data stratified 'by' some variables. 2) LSmeans (least-squares means), general linear estimates. 3) Restrict functions to a smaller domain. 4) Miscellaneous other utilities.

Maintained by Søren Højsgaard. Last updated 23 hours ago.

1 stars 14.99 score 3.2k scripts 948 dependents

guido-s

meta:General Package for Meta-Analysis

User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - common effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - three-level meta-analysis model; - generalised linear mixed model; - logistic regression with penalised likelihood for rare events; - Hartung-Knapp method for random effects model; - Kenward-Roger method for random effects model; - prediction interval; - statistical tests for funnel plot asymmetry; - trim-and-fill method to evaluate bias in meta-analysis; - meta-regression; - cumulative meta-analysis and leave-one-out meta-analysis; - import data from 'RevMan 5'; - produce forest plot summarising several (subgroup) meta-analyses.

Maintained by Guido Schwarzer. Last updated 3 days ago.

meta-analysis rstudio

89 stars 14.95 score 2.3k scripts 30 dependents

bioc

MultiAssayExperiment:Software for the integration of multi-omics experiments in Bioconductor

Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames. Facilities are provided for reshaping data into wide and long formats for adaptability to graphing and downstream analysis.

Maintained by Marcel Ramos. Last updated 2 months ago.

infrastructure datarepresentation bioconductor bioconductor-package genomics nci-itcr tcga u24ca289073

71 stars 14.94 score 670 scripts 126 dependents

philchalmers

mirt:Multidimensional Item Response Theory

Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported, as well as a wide family of probabilistic unfolding models.

Maintained by Phil Chalmers. Last updated 4 days ago.

irt mirt openblas cpp openmp

212 stars 14.93 score 2.5k scripts 40 dependents

cynkra

dm:Relational Data Models

Provides tools for working with multiple related tables, stored as data frames or in a relational database. Multiple tables (data and metadata) are stored in a compound object, which can then be manipulated with a pipe-friendly syntax.

Maintained by Kirill Müller. Last updated 3 months ago.

data-model data-warehousing datawarehousing dbi dbplyr relational-databases

511 stars 14.81 score 410 scripts 8 dependents

bioc

GSVA:Gene Set Variation Analysis for Microarray and RNA-Seq Data

Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene-set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric manner.

Maintained by Robert Castelo. Last updated 10 days ago.

functionalgenomics microarray rnaseq pathways genesetenrichment gene-set-enrichment genomics pathway-enrichment-analysis

212 stars 14.74 score 1.6k scripts 19 dependents

florianhartig

DHARMa:Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models

The 'DHARMa' package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed models. Currently supported are linear and generalized linear (mixed) models from 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB', 'GLMMadaptive', and 'spaMM'; phylogenetic linear models from 'phylolm' (classes 'phylolm' and 'phyloglm'); generalized additive models ('gam' from 'mgcv'); 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial, phylogenetic and temporal autocorrelation.

Maintained by Florian Hartig. Last updated 27 days ago.

glmm regression regression-diagnostics residual

226 stars 14.74 score 2.8k scripts 10 dependents

thomasp85

tidygraph:A Tidy API for Graph Manipulation

A graph, while not "tidy" in itself, can be thought of as two tidy data frames describing node and edge data respectively. 'tidygraph' provides an approach to manipulate these two virtual data frames using the API defined in the 'dplyr' package, as well as provides tidy interfaces to a lot of common graph algorithms.

Maintained by Thomas Lin Pedersen. Last updated 2 months ago.

graph-algorithms graph-manipulation igraph network-analysis tidyverse cpp

553 stars 14.74 score 4.6k scripts 136 dependents

mjskay

tidybayes:Tidy Data and 'Geoms' for Bayesian Models

Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided to help extract tidy data frames of draws from Bayesian models and that generate point summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus densities), and fit curves with multiple, arbitrary uncertainty bands.

Maintained by Matthew Kay. Last updated 7 months ago.

bayesian-data-analysis brms ggplot2 jags stan tidy-data visualization

733 stars 14.72 score 7.3k scripts 20 dependents

husson

FactoMineR:Multivariate Exploratory Data Analysis and Data Mining

Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).

Maintained by Francois Husson. Last updated 4 months ago.

47 stars 14.71 score 5.6k scripts 112 dependents

dcomtois

summarytools:Tools to Quickly and Neatly Summarize Data

Data frame summaries, cross-tabulations, weight-enabled frequency tables and common descriptive (univariate) statistics in concise tables available in a variety of formats (plain ASCII, Markdown and HTML). A good point-of-entry for exploring data, both for experienced and new R users.

Maintained by Dominic Comtois. Last updated 6 days ago.

descriptive-statistics frequency-table html-report markdown pander pandoc pandoc-markdown rmarkdown rstudio

527 stars 14.62 score 2.9k scripts 6 dependents

sinhrks

ggfortify:Data Visualization Tools for Statistical Analysis Results

Unified plotting tools for statistics commonly used, such as GLM, time series, PCA families, clustering and survival analysis. The package offers a single plotting interface for these analysis results and plots in a unified style using 'ggplot2'.

Maintained by Yuan Tang. Last updated 9 months ago.

528 stars 14.60 score 9.1k scripts 24 dependents

hojsgaard

pbkrtest:Parametric Bootstrap, Kenward-Roger and Satterthwaite Based Methods for Test in Mixed Models

Computes p-values based on (a) Satterthwaite or Kenward-Rogers degree of freedom methods and (b) parametric bootstrap for mixed effects models as implemented in the 'lme4' package. Implements parametric bootstrap test for generalized linear mixed models as implemented in 'lme4' and generalized linear models. The package is documented in the paper by Halekoh and Højsgaard, (2012, <doi:10.18637/jss.v059.i09>). Please see 'citation("pbkrtest")' for citation details.

Maintained by Søren Højsgaard. Last updated 18 hours ago.

6 stars 14.53 score 648 scripts 929 dependents

jacob-long

jtools:Analysis and Presentation of Social Scientific Data

This is a collection of tools for more efficiently understanding and sharing the results of (primarily) regression analyses. There are also a number of miscellaneous functions for statistical and programming purposes. Support for models produced by the survey and lme4 packages are points of emphasis.

Maintained by Jacob A. Long. Last updated 7 months ago.

social-sciences

167 stars 14.48 score 4.0k scripts 14 dependents

tidyverts

tsibble:Tidy Temporal Data Frames and Tools

Provides a 'tbl_ts' class (the 'tsibble') for temporal data in an data- and model-oriented format. The 'tsibble' provides tools to easily manipulate and analyse temporal data, such as filling in time gaps and aggregating over calendar periods.

Maintained by Earo Wang. Last updated 2 months ago.

536 stars 14.48 score 4.4k scripts 42 dependents

bioc

TCGAbiolinks:TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data

The aim of TCGAbiolinks is : i) facilitate the GDC open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses and iv) to easily reproduce earlier research results. In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.

Maintained by Tiago Chedraoui Silva. Last updated 1 months ago.

dnamethylation differentialmethylation generegulation geneexpression methylationarray differentialexpression pathways network sequencing survival software bioc bioconductor gdc integrative-analysis tcga tcga-data tcgabiolinks

310 stars 14.47 score 1.6k scripts 6 dependents

indrajeetpatil

ggstatsplot:'ggplot2' Based Plots with Statistical Details

Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses. References: Patil (2021) <doi:10.21105/joss.03236>.

Maintained by Indrajeet Patil. Last updated 1 months ago.

bayes-factors datascience dataviz effect-size ggplot-extension hypothesis-testing non-parametric-statistics regression-models statistical-analysis

2.1k stars 14.46 score 3.0k scripts 1 dependents

statistikat

VIM:Visualization and Imputation of Missing Values

New tools for the visualization of missing and/or imputed values are introduced, which can be used for exploring the data and the structure of the missing and/or imputed values. Depending on this structure of the missing values, the corresponding methods may help to identify the mechanism generating the missing values and allows to explore the data including missing values. In addition, the quality of imputation can be visually explored using various univariate, bivariate, multiple and multivariate plot methods. A graphical user interface available in the separate package VIMGUI allows an easy handling of the implemented plot methods.

Maintained by Matthias Templ. Last updated 8 months ago.

hotdeck imputation-methods model-predictions visualization cpp

85 stars 14.44 score 2.6k scripts 19 dependents

singmann

afex:Analysis of Factorial Experiments

Convenience functions for analyzing factorial experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated-measures), or mixed (i.e., split-plot) ANOVAs for data in long format (i.e., one observation per row), automatically aggregating multiple observations per individual and cell of the design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger or Satterthwaite approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). afex_plot() provides a high-level interface for interaction or one-way plots using ggplot2, combining raw data and model estimates. afex uses type 3 sums of squares as default (imitating commercial statistical software).

Maintained by Henrik Singmann. Last updated 7 months ago.

124 stars 14.43 score 1.4k scripts 15 dependents

tidymodels

dials:Tools for Creating Tuning Parameter Values

Many models contain tuning parameters (i.e. parameters that cannot be directly estimated from the data). These tools can be used to define objects for creating, simulating, or validating values for such parameters.

Maintained by Hannah Frick. Last updated 2 months ago.

114 stars 14.31 score 426 scripts 52 dependents

bioc

xcms:LC-MS and GC-MS Data Analysis

Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.

Maintained by Steffen Neumann. Last updated 17 days ago.

immunooncology massspectrometry metabolomics bioconductor feature-detection mass-spectrometry peak-detection cpp

196 stars 14.31 score 984 scripts 11 dependents

tidymodels

tune:Tidy Tuning Tools

The ability to tune models is important. 'tune' contains functions and classes to be used in conjunction with other 'tidymodels' packages for finding reasonable values of hyper-parameters in models, pre-processing methods, and post-processing steps.

Maintained by Max Kuhn. Last updated 27 days ago.

293 stars 14.27 score 756 scripts 39 dependents

talgalili

heatmaply:Interactive Cluster Heat Maps Using 'plotly' and 'ggplot2'

Create interactive cluster 'heatmaps' that can be saved as a stand- alone HTML file, embedded in 'R Markdown' documents or in a 'Shiny' app, and available in the 'RStudio' viewer pane. Hover the mouse pointer over a cell to show details or drag a rectangle to zoom. A 'heatmap' is a popular graphical method for visualizing high-dimensional data, in which a table of numbers are encoded as a grid of colored cells. The rows and columns of the matrix are ordered to highlight patterns and are often accompanied by 'dendrograms'. 'Heatmaps' are used in many fields for visualizing observations, correlations, missing values patterns, and more. Interactive 'heatmaps' allow the inspection of specific value by hovering the mouse over a cell, as well as zooming into a region of the 'heatmap' by dragging a rectangle around the relevant area. This work is based on the 'ggplot2' and 'plotly.js' engine. It produces similar 'heatmaps' to 'heatmap.2' with the advantage of speed ('plotly.js' is able to handle larger size matrix), the ability to zoom from the 'dendrogram' panes, and the placing of factor variables in the sides of the 'heatmap'.

Maintained by Tal Galili. Last updated 9 months ago.

d3-heatmap dendextend dendrogram ggplot2 heatmap plotly

386 stars 14.21 score 2.0k scripts 45 dependents

business-science

timetk:A Tool Kit for Working with Time Series

Easy visualization, wrangling, and feature engineering of time series data for forecasting and machine learning prediction. Consolidates and extends time series functionality from packages including 'dplyr', 'stats', 'xts', 'forecast', 'slider', 'padr', 'recipes', and 'rsample'.

Maintained by Matt Dancho. Last updated 1 years ago.

coercion coercion-functions data-mining dplyr forecast forecasting forecasting-models machine-learning series-decomposition series-signature tibble tidy tidyquant tidyverse time time-series timeseries

626 stars 14.20 score 4.0k scripts 16 dependents

dkahle

ggmap:Spatial Visualization with ggplot2

A collection of functions to visualize spatial data and models on top of static maps from various online sources (e.g Google Maps and Stamen Maps). It includes tools common to those tasks, including functions for geolocation and routing.

Maintained by David Kahle. Last updated 1 years ago.

770 stars 14.17 score 12k scripts 31 dependents

doi-usgs

dataRetrieval:Retrieval Functions for USGS and EPA Hydrology and Water Quality Data

Collection of functions to help retrieve U.S. Geological Survey and U.S. Environmental Protection Agency water quality and hydrology data from web services. Data are discovered from National Water Information System <https://waterservices.usgs.gov/> and <https://waterdata.usgs.gov/nwis>. Water quality data are obtained from the Water Quality Portal <https://www.waterqualitydata.us/>.

Maintained by Laura DeCicco. Last updated 5 days ago.

usgs

286 stars 14.16 score 1.7k scripts 15 dependents

corybrunson

ggalluvial:Alluvial Plots in 'ggplot2'

Alluvial plots use variable-width ribbons and stacked bar plots to represent multi-dimensional or repeated-measures data with categorical or ordinal variables; see Riehmann, Hanfler, and Froehlich (2005) <doi:10.1109/INFVIS.2005.1532152> and Rosvall and Bergstrom (2010) <doi:10.1371/journal.pone.0008694>. Alluvial plots are statistical graphics in the sense of Wilkinson (2006) <doi:10.1007/0-387-28695-0>; they share elements with Sankey diagrams and parallel sets plots but are uniquely determined from the data and a small set of parameters. This package extends Wickham's (2010) <doi:10.1198/jcgs.2009.07098> layered grammar of graphics to generate alluvial plots from tidy data.

Maintained by Jason Cory Brunson. Last updated 8 months ago.

alluvial-diagrams alluvial-plots categorical-data-visualization ggplot2 repeated-measures-data

507 stars 14.14 score 3.0k scripts 21 dependents

kassambara

factoextra:Extract and Visualize the Results of Multivariate Data Analyses

Provides some easy-to-use functions to extract and visualize the output of multivariate data analyses, including 'PCA' (Principal Component Analysis), 'CA' (Correspondence Analysis), 'MCA' (Multiple Correspondence Analysis), 'FAMD' (Factor Analysis of Mixed Data), 'MFA' (Multiple Factor Analysis) and 'HMFA' (Hierarchical Multiple Factor Analysis) functions from different R packages. It contains also functions for simplifying some clustering analysis steps and provides 'ggplot2' - based elegant data visualization.

Maintained by Alboukadel Kassambara. Last updated 5 years ago.

363 stars 14.13 score 15k scripts 52 dependents

walkerke

tidycensus:Load US Census Boundary and Attribute Data as 'tidyverse' and 'sf'-Ready Data Frames

An integrated R interface to several United States Census Bureau APIs (<https://www.census.gov/data/developers/data-sets.html>) and the US Census Bureau's geographic boundary files. Allows R users to return Census and ACS data as tidyverse-ready data frames, and optionally returns a list-column with feature geometry for mapping and spatial analysis.

Maintained by Kyle Walker. Last updated 2 months ago.

648 stars 14.02 score 7.5k scripts 10 dependents

pharmaverse

admiral:ADaM in R Asset Library

A toolbox for programming Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, <https://www.cdisc.org/standards/foundational/adam>).

Maintained by Ben Straub. Last updated 6 days ago.

cdisc clinical-trials open-source

239 stars 13.97 score 486 scripts 4 dependents

tidymodels

workflows:Modeling Workflows

Managing both a 'parsnip' model and a preprocessor, such as a model formula or recipe from 'recipes', can often be challenging. The goal of 'workflows' is to streamline this process by bundling the model alongside the preprocessor, all within the same object.

Maintained by Simon Couch. Last updated 1 months ago.

207 stars 13.97 score 876 scripts 43 dependents

hughjonesd

huxtable:Easily Create and Style Tables for LaTeX, HTML and Other Formats

Creates styled tables for data presentation. Export to HTML, LaTeX, RTF, 'Word', 'Excel', and 'PowerPoint'. Simple, modern interface to manipulate borders, size, position, captions, colours, text styles and number formatting. Table cells can span multiple rows and/or columns. Includes a 'huxreg' function for creation of regression tables, and 'quick_*' one-liners to print data to a new document.

Maintained by David Hugh-Jones. Last updated 27 days ago.

html huxtable latex microsoft-word powerpoint reproducible-research tables

323 stars 13.93 score 1.9k scripts 16 dependents

jbkunst

highcharter:A Wrapper for the 'Highcharts' Library

A wrapper for the 'Highcharts' library including shortcut functions to plot R objects. 'Highcharts' <https://www.highcharts.com/> is a charting library offering numerous chart types with a simple configuration syntax.

Maintained by Joshua Kunst. Last updated 1 years ago.

highcharts htmlwidgets shiny shiny-r visualization wrapper

725 stars 13.93 score 4.9k scripts 18 dependents

bioc

AnnotationHub:Client to access AnnotationHub resources

This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, Ensembl) can be discovered. The resource includes metadata about each resource, e.g., a textual description, tags, and date of modification. The client creates and manages a local cache of files retrieved by the user, helping with quick and reproducible access.

Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.

infrastructure dataimport gui thirdpartyclient core-package u24ca289073

17 stars 13.88 score 2.7k scripts 104 dependents

gergness

srvyr:'dplyr'-Like Syntax for Summary Statistics of Survey Data

Use piping, verbs like 'group_by' and 'summarize', and other 'dplyr' inspired syntactic style when calculating summary statistics on survey data using functions from the 'survey' package.

Maintained by Greg Freedman Ellis. Last updated 2 months ago.

survey

215 stars 13.88 score 1.8k scripts 15 dependents

biomodhub

biomod2:Ensemble Platform for Species Distribution Modeling

Functions for species distribution modeling, calibration and evaluation, ensemble of models, ensemble forecasting and visualization. The package permits to run consistently up to 10 single models on a presence/absences (resp presences/pseudo-absences) dataset and to combine them in ensemble models and ensemble projections. Some bench of other evaluation and visualisation tools are also available within the package.

Maintained by Maya Guéguen. Last updated 1 hours ago.

95 stars 13.85 score 536 scripts 7 dependents

tidymodels

corrr:Correlations in R

A tool for exploring correlations. It makes it possible to easily perform routine tasks when exploring correlation matrices such as ignoring the diagonal, focusing on the correlations of certain variables against others, or rearranging and visualizing the matrix in terms of the strength of the correlations.

Maintained by Max Kuhn. Last updated 1 years ago.

593 stars 13.82 score 2.9k scripts 7 dependents

bioc

BiocFileCache:Manage Files Across Sessions

This package creates a persistent on-disk cache of files that the user can add, update, and retrieve. It is useful for managing resources (such as custom Txdb objects) that are costly or difficult to create, web resources, and data files used across sessions.

Maintained by Lori Shepherd. Last updated 2 months ago.

dataimport core-package u24ca289073

13 stars 13.76 score 486 scripts 436 dependents

bioc

mixOmics:Omics Data Integration Project

Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducing the dimension of the data by using instrumental variables (components), which are defined as combinations of all variables. Those components are then used to produce useful graphical outputs that enable better understanding of the relationships and correlation structures between the different data sets that are integrated. mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data. A non exhaustive list of methods include variants of generalised Canonical Correlation Analysis, sparse Partial Least Squares and sparse Discriminant Analysis. Recently we implemented integrative methods to combine multiple data sets: N-integration with variants of Generalised Canonical Correlation Analysis and P-integration with variants of multi-group Partial Least Squares.

Maintained by Eva Hamrud. Last updated 3 days ago.

immunooncology microarray sequencing metabolomics metagenomics proteomics geneprediction multiplecomparison classification regression bioconductor genomics genomics-data genomics-visualization multivariate-analysis multivariate-statistics omics r-pkg r-project

185 stars 13.75 score 1.3k scripts 22 dependents

immunogenomics

harmony:Fast, Sensitive, and Accurate Integration of Single Cell Data

Implementation of the Harmony algorithm for single cell integration, described in Korsunsky et al <doi:10.1038/s41592-019-0619-0>. Package includes a standalone Harmony function and interfaces to external frameworks.

Maintained by Ilya Korsunsky. Last updated 5 months ago.

algorithm data-integration scrna-seq openblas cpp

554 stars 13.74 score 5.5k scripts 8 dependents

knausb

vcfR:Manipulate and Visualize VCF Data

Facilitates easy manipulation of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices of data. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file (*.vcf.gz). It also may be converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and familiar R software.

Maintained by Brian J. Knaus. Last updated 1 months ago.

genomics population-genetics population-genomics rcpp vcf-data visualization zlib cpp

256 stars 13.66 score 3.1k scripts 19 dependents

aphalo

ggpmisc:Miscellaneous Extensions to 'ggplot2'

Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Statistics: locate and tag peaks and valleys; label plot with the equation of a fitted polynomial or other types of models; labels with P-value, R^2 or adjusted R^2 or information criteria for fitted models; label with ANOVA table for fitted models; label with summary for fitted models. Model fit classes for which suitable methods are provided by package 'broom' and 'broom.mixed' are supported. Scales and stats to build volcano and quadrant plots based on outcomes, fold changes, p-values and false discovery rates.

Maintained by Pedro J. Aphalo. Last updated 2 days ago.

data-analysis dataviz ggplot2-annotations ggplot2-stats statistics

107 stars 13.64 score 4.4k scripts 14 dependents

ropensci

taxize:Taxonomic Information from Around the Web

Interacts with a suite of web application programming interfaces (API) for taxonomic tasks, such as getting database specific taxonomic identifiers, verifying species names, getting taxonomic hierarchies, fetching downstream and upstream taxonomic names, getting taxonomic synonyms, converting scientific to common names and vice versa, and more. Some of the services supported include 'NCBI E-utilities' (<https://www.ncbi.nlm.nih.gov/books/NBK25501/>), 'Encyclopedia of Life' (<https://eol.org/docs/what-is-eol/data-services>), 'Global Biodiversity Information Facility' (<https://techdocs.gbif.org/en/openapi/>), and many more. Links to the API documentation for other supported services are available in the documentation for their respective functions in this package.

Maintained by Zachary Foster. Last updated 27 days ago.

taxonomy biology nomenclature json api web api-client identifiers species names api-wrapper biodiversity darwincore data taxize

274 stars 13.63 score 1.6k scripts 23 dependents

rstudio

keras3:R Interface to 'Keras'

Interface to 'Keras' <https://keras.io>, a high-level neural networks API. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both CPU and GPU devices.

Maintained by Tomasz Kalinowski. Last updated 11 days ago.

845 stars 13.63 score 264 scripts 2 dependents

yulab-smu

scatterpie:Scatter Pie Plot

Creates scatterpie plots, especially useful for plotting pies on a map.

Maintained by Guangchuang Yu. Last updated 3 months ago.

62 stars 13.60 score 820 scripts 68 dependents

dieghernan

tidyterra:'tidyverse' Methods and 'ggplot2' Helpers for 'terra' Objects

Extension of the 'tidyverse' for 'SpatRaster' and 'SpatVector' objects of the 'terra' package. It includes also new 'geom_' functions that provide a convenient way of visualizing 'terra' objects with 'ggplot2'.

Maintained by Diego Hernangómez. Last updated 20 hours ago.

terra ggplot-extension r-spatial rspatial

190 stars 13.59 score 1.9k scripts 26 dependents

kaz-yos

tableone:Create 'Table 1' to Describe Baseline Characteristics with or without Propensity Score Weights

Creates 'Table 1', i.e., description of baseline patient characteristics, which is essential in every medical research. Supports both continuous and categorical variables, as well as p-values and standardized mean differences. Weighted data are supported via the 'survey' package.

Maintained by Kazuki Yoshida. Last updated 3 years ago.

baseline-characteristics descriptive-statistics statistics

221 stars 13.55 score 2.3k scripts 12 dependents

tidyverts

fable:Forecasting Models for Tidy Time Series

Provides a collection of commonly used univariate and multivariate time series forecasting models including automatically selected exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA) models. These models work within the 'fable' framework provided by the 'fabletools' package, which provides the tools to evaluate, visualise, and combine models in a workflow consistent with the tidyverse.

Maintained by Mitchell OHara-Wild. Last updated 4 months ago.

forecasting cpp

569 stars 13.54 score 2.1k scripts 6 dependents

bioc

GEOquery:Get data from NCBI Gene Expression Omnibus (GEO)

The NCBI Gene Expression Omnibus (GEO) is a public repository of microarray data. Given the rich and varied nature of this resource, it is only natural to want to apply BioConductor tools to these data. GEOquery is the bridge between GEO and BioConductor.

Maintained by Sean Davis. Last updated 5 months ago.

microarray dataimport onechannel twochannel sage bioconductor bioinformatics data-science genomics ncbi-geo

93 stars 13.48 score 4.1k scripts 45 dependents

philchalmers

SimDesign:Structure for Organizing Monte Carlo Simulation Designs

Provides tools to safely and efficiently organize and execute Monte Carlo simulation experiments in R. The package controls the structure and back-end of Monte Carlo simulation experiments by utilizing a generate-analyse-summarise workflow. The workflow safeguards against common simulation coding issues, such as automatically re-simulating non-convergent results, prevents inadvertently overwriting simulation files, catches error and warning messages during execution, implicitly supports parallel processing with high-quality random number generation, and provides tools for managing high-performance computing (HPC) array jobs submitted to schedulers such as SLURM. For a pedagogical introduction to the package see Sigal and Chalmers (2016) <doi:10.1080/10691898.2016.1246953>. For a more in-depth overview of the package and its design philosophy see Chalmers and Adkins (2020) <doi:10.20982/tqmp.16.4.p248>.

Maintained by Phil Chalmers. Last updated 3 days ago.

monte-carlo-simulation simulation simulation-framework

62 stars 13.41 score 253 scripts 47 dependents

yulab-smu

tidytree:A Tidy Tool for Phylogenetic Tree Data Manipulation

Phylogenetic tree generally contains multiple components including node, edge, branch and associated data. 'tidytree' provides an approach to convert tree object to tidy data frame as well as provides tidy interfaces to manipulate tree data.

Maintained by Guangchuang Yu. Last updated 8 months ago.

phylogenetic-tree tidyverse tree-data

56 stars 13.36 score 584 scripts 128 dependents

business-science

tidyquant:Tidy Quantitative Financial Analysis

Bringing business and financial analysis to the 'tidyverse'. The 'tidyquant' package provides a convenient wrapper to various 'xts', 'zoo', 'quantmod', 'TTR' and 'PerformanceAnalytics' package functions and returns the objects in the tidy 'tibble' format. The main advantage is being able to use quantitative functions with the 'tidyverse' functions including 'purrr', 'dplyr', 'tidyr', 'ggplot2', 'lubridate', etc. See the 'tidyquant' website for more information, documentation and examples.

Maintained by Matt Dancho. Last updated 2 months ago.

dplyr financial-analysis financial-data financial-statements multiple-stocks performance-analysis performanceanalytics quantmod stock stock-exchanges stock-indexes stock-lists stock-performance stock-prices stock-symbol tidyverse time-series timeseries xts

872 stars 13.34 score 5.2k scripts

projectmosaic

mosaic:Project MOSAIC Statistics and Mathematics Teaching Utilities

Data sets and utilities from Project MOSAIC (<http://www.mosaic-web.org>) used to teach mathematics, statistics, computation and modeling. Funded by the NSF, Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.

Maintained by Randall Pruim. Last updated 1 years ago.

93 stars 13.32 score 7.2k scripts 7 dependents

ropensci

visdat:Preliminary Visualisation of Data

Create preliminary exploratory data visualisations of an entire dataset to identify problems or unexpected features using 'ggplot2'.

Maintained by Nicholas Tierney. Last updated 9 months ago.

exploratory-data-analysis missingness peer-reviewed ropensci visualisation

452 stars 13.31 score 2.1k scripts 11 dependents

chjackson

flexsurv:Flexible Parametric Survival and Multi-State Models

Flexible parametric models for time-to-event data, including the Royston-Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution can be fitted, given at least an R function defining the probability density or hazard. There are also tools for fitting and predicting from fully parametric multi-state models, based on either cause-specific hazards or mixture models.

Maintained by Christopher Jackson. Last updated 2 months ago.

cpp

57 stars 13.31 score 632 scripts 43 dependents

dreamrs

esquisse:Explore and Visualize Your Data Interactively

A 'shiny' gadget to create 'ggplot2' figures interactively with drag-and-drop to map your variables to different aesthetics. You can quickly visualize your data accordingly to their type, export in various formats, and retrieve the code to reproduce the plot.

Maintained by Victor Perrier. Last updated 1 months ago.

addin data-visualization ggplot2 rstudio-addin visualization

1.8k stars 13.31 score 1.1k scripts 1 dependents

oscarkjell

text:Analyses of Text using Transformers Models from HuggingFace, Natural Language Processing and Machine Learning

Link R with Transformers from Hugging Face to transform text variables to word embeddings; where the word embeddings are used to statistically test the mean difference between set of texts, compute semantic similarity scores between texts, predict numerical variables, and visual statistically significant words according to various dimensions etc. For more information see <https://www.r-text.org>.

Maintained by Oscar Kjell. Last updated 9 days ago.

deep-learning machine-learning nlp transformers openjdk

145 stars 13.21 score 436 scripts 1 dependents

wadpac

GGIR:Raw Accelerometer Data Analysis

A tool to process and analyse data collected with wearable raw acceleration sensors as described in Migueles and colleagues (JMPB 2019), and van Hees and colleagues (JApplPhysiol 2014; PLoSONE 2015). The package has been developed and tested for binary data from 'GENEActiv' <https://activinsights.com/>, binary (.gt3x) and .csv-export data from 'Actigraph' <https://theactigraph.com> devices, and binary (.cwa) and .csv-export data from 'Axivity' <https://axivity.com>. These devices are currently widely used in research on human daily physical activity. Further, the package can handle accelerometer data file from any other sensor brand providing that the data is stored in csv format. Also the package allows for external function embedding.

Maintained by Vincent T van Hees. Last updated 17 days ago.

accelerometer activity-recognition circadian-rhythm movement-sensor sleep

109 stars 13.20 score 342 scripts 3 dependents

stan-dev

shinystan:Interactive Visual and Numerical Diagnostics and Posterior Analysis for Bayesian Models

A graphical user interface for interactive Markov chain Monte Carlo (MCMC) diagnostics and plots and tables helpful for analyzing a posterior sample. The interface is powered by the 'Shiny' web application framework from 'RStudio' and works with the output of MCMC programs written in any programming language (and has extended functionality for 'Stan' models fit using the 'rstan' and 'rstanarm' packages).

Maintained by Jonah Gabry. Last updated 3 years ago.

bayesian bayesian-data-analysis bayesian-inference bayesian-methods bayesian-statistics mcmc shiny-apps stan statistical-graphics

200 stars 13.13 score 1.6k scripts 15 dependents

larmarange

ggstats:Extension to 'ggplot2' for Plotting Stats

Provides new statistics, new geometries and new positions for 'ggplot2' and a suite of functions to facilitate the creation of statistical plots.

Maintained by Joseph Larmarange. Last updated 21 days ago.

37 stars 13.08 score 190 scripts 156 dependents

keaven

gsDesign:Group Sequential Design

Derives group sequential clinical trial designs and describes their properties. Particular focus on time-to-event, binary, and continuous outcomes. Largely based on methods described in Jennison, Christopher and Turnbull, Bruce W., 2000, "Group Sequential Methods with Applications to Clinical Trials" ISBN: 0-8493-0316-8.

Maintained by Keaven Anderson. Last updated 27 days ago.

biostatistics boundaries clinical-trials design spending-functions

51 stars 13.05 score 338 scripts 5 dependents

bioc

Gviz:Plotting data and annotation information along genomic coordinates

Genomic data analyses requires integrated visualization of known genomic information and new experimental data. Gviz uses the biomaRt and the rtracklayer packages to perform live annotation queries to Ensembl and UCSC and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data.

Maintained by Robert Ivanek. Last updated 5 months ago.

visualization microarray sequencing

79 stars 13.05 score 1.4k scripts 46 dependents

bioc

ChIPseeker:ChIPseeker for ChIP peak Annotation, Comparison, and Visualization

This package implements functions to retrieve the nearest genes around the peak, annotate genomic region of the peak, statstical methods for estimate the significance of overlap among ChIP peak data sets, and incorporate GEO database for user to compare the own dataset with those deposited in database. The comparison can be used to infer cooperative regulation and thus can be used to generate hypotheses. Several visualization functions are implemented to summarize the coverage of the peak experiment, average profile and heatmap of peaks binding to TSS regions, genomic annotation, distance to TSS, and overlap of peaks or genes.

Maintained by Guangchuang Yu. Last updated 5 months ago.

annotation chipseq software visualization multiplecomparison atac-seq chip-seq comparison epigenetics epigenomics

233 stars 13.05 score 1.6k scripts 5 dependents

gavinsimpson

gratia:Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'

Graceful 'ggplot'-based graphics and utility functions for working with generalized additive models (GAMs) fitted using the 'mgcv' package. Provides a reimplementation of the plot() method for GAMs that 'mgcv' provides, as well as 'tidyverse' compatible representations of estimated smooths.

Maintained by Gavin L. Simpson. Last updated 15 days ago.

distributional-regression gam gamm generalized-additive-mixed-models generalized-additive-models ggplot2 glm lm mgcv penalized-spline random-effects smoothing splines

217 stars 12.99 score 1.6k scripts 2 dependents

dgrtwo

fuzzyjoin:Join Tables Together on Inexact Matching

Join tables together based not on whether columns match exactly, but whether they are similar by some comparison. Implementations include string distance and regular expression matching.

Maintained by David Robinson. Last updated 5 years ago.

679 stars 12.96 score 1.5k scripts 21 dependents

openair-project

openair:Tools for the Analysis of Air Pollution Data

Tools to analyse, interpret and understand air pollution data. Data are typically regular time series and air quality measurement, meteorological data and dispersion model output can be analysed. The package is described in Carslaw and Ropkins (2012, <doi:10.1016/j.envsoft.2011.09.008>) and subsequent papers.

Maintained by David Carslaw. Last updated 3 days ago.

air-quality air-quality-data meteorology openair cpp

316 stars 12.94 score 1.2k scripts 12 dependents

juba

questionr:Functions to Make Surveys Processing Easier

Set of functions to make the processing and analysis of surveys easier : interactive shiny apps and addins for data recoding, contingency tables, dataset metadata handling, and several convenience functions.

Maintained by Julien Barnier. Last updated 10 days ago.

83 stars 12.93 score 1.1k scripts 19 dependents

mjockers

syuzhet:Extracts Sentiment and Sentiment-Derived Plot Arcs from Text

Extracts sentiment and sentiment-derived plot arcs from text using a variety of sentiment dictionaries conveniently packaged for consumption by R users. Implemented dictionaries include "syuzhet" (default) developed in the Nebraska Literary Lab "afinn" developed by Finn Årup Nielsen, "bing" developed by Minqing Hu and Bing Liu, and "nrc" developed by Mohammad, Saif M. and Turney, Peter D. Applicable references are available in README.md and in the documentation for the "get_sentiment" function. The package also provides a hack for implementing Stanford's coreNLP sentiment parser. The package provides several methods for plot arc normalization.

Maintained by Matthew Jockers. Last updated 2 years ago.

336 stars 12.92 score 1.4k scripts 31 dependents

friendly

matlib:Matrix Functions for Teaching and Learning Linear Algebra and Multivariate Statistics

A collection of matrix functions for teaching and learning matrix linear algebra as used in multivariate statistical methods. Many of these functions are designed for tutorial purposes in learning matrix algebra ideas using R. In some cases, functions are provided for concepts available elsewhere in R, but where the function call or name is not obvious. In other cases, functions are provided to show or demonstrate an algorithm. In addition, a collection of functions are provided for drawing vector diagrams in 2D and 3D and for rendering matrix expressions and equations in LaTeX.

Maintained by Michael Friendly. Last updated 16 days ago.

diagrams linear-equations matrix matrix-functions matrix-visualizer vector vignette

65 stars 12.89 score 900 scripts 11 dependents

walkerke

tigris:Load Census TIGER/Line Shapefiles

Download TIGER/Line shapefiles from the United States Census Bureau (<https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html>) and load into R as 'sf' objects.

Maintained by Kyle Walker. Last updated 5 months ago.

331 stars 12.87 score 5.3k scripts 16 dependents

paleolimbot

ggspatial:Spatial Data Framework for ggplot2

Spatial data plus the power of the ggplot2 framework means easier mapping when input data are already in the form of spatial objects.

Maintained by Dewey Dunnington. Last updated 2 years ago.

379 stars 12.85 score 4.1k scripts 24 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

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 17 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

plyranges:A fluent interface for manipulating GenomicRanges

A dplyr-like interface for interacting with the common Bioconductor classes Ranges and GenomicRanges. By providing a grammatical and consistent way of manipulating these classes their accessiblity for new Bioconductor users is hopefully increased.

Maintained by Michael Love. Last updated 12 days ago.

infrastructure datarepresentation workflowstep coverage bioconductor data-analysis dplyr genomic-ranges genomics tidy-data

144 stars 12.66 score 1.9k scripts 20 dependents

insightsengineering

teal:Exploratory Web Apps for Analyzing Clinical Trials Data

A 'shiny' based interactive exploration framework for analyzing clinical trials data. 'teal' currently provides a dynamic filtering facility and different data viewers. 'teal' 'shiny' applications are built using standard 'shiny' modules.

Maintained by Dawid Kaledkowski. Last updated 1 months ago.

clinical-trials nest shiny webapp

206 stars 12.65 score 176 scripts 5 dependents

bioc

SpatialExperiment:S4 Class for Spatially Resolved -omics Data

Defines an S4 class for storing data from spatial -omics experiments. The class extends SingleCellExperiment to support storage and retrieval of additional information from spot-based and molecule-based platforms, including spatial coordinates, images, and image metadata. A specialized constructor function is included for data from the 10x Genomics Visium platform.

Maintained by Dario Righelli. Last updated 5 months ago.

datarepresentation dataimport infrastructure immunooncology geneexpression transcriptomics singlecell spatial

59 stars 12.63 score 1.8k scripts 71 dependents

ohdsi

DatabaseConnector:Connecting to Various Database Platforms

An R 'DataBase Interface' ('DBI') compatible interface to various database platforms ('PostgreSQL', 'Oracle', 'Microsoft SQL Server', 'Amazon Redshift', 'Microsoft Parallel Database Warehouse', 'IBM Netezza', 'Apache Impala', 'Google BigQuery', 'Snowflake', 'Spark', 'SQLite', and 'InterSystems IRIS'). Also includes support for fetching data as 'Andromeda' objects. Uses either 'Java Database Connectivity' ('JDBC') or other 'DBI' drivers to connect to databases.

Maintained by Martijn Schuemie. Last updated 2 months ago.

hades openjdk

56 stars 12.63 score 772 scripts 11 dependents

wesm

feather:R Bindings to the Feather 'API'

Read and write feather files, a lightweight binary columnar data store designed for maximum speed.

Maintained by Hadley Wickham. Last updated 4 years ago.

2.7k stars 12.61 score 3.9k scripts 5 dependents

thibautjombart

adegenet:Exploratory Analysis of Genetic and Genomic Data

Toolset for the exploration of genetic and genomic data. Adegenet provides formal (S4) classes for storing and handling various genetic data, including genetic markers with varying ploidy and hierarchical population structure ('genind' class), alleles counts by populations ('genpop'), and genome-wide SNP data ('genlight'). It also implements original multivariate methods (DAPC, sPCA), graphics, statistical tests, simulation tools, distance and similarity measures, and several spatial methods. A range of both empirical and simulated datasets is also provided to illustrate various methods.

Maintained by Zhian N. Kamvar. Last updated 2 months ago.

182 stars 12.60 score 1.9k scripts 29 dependents

hrbrmstr

ggalt:Extra Coordinate Systems, 'Geoms', Statistical Transformations, Scales and Fonts for 'ggplot2'

A compendium of new geometries, coordinate systems, statistical transformations, scales and fonts for 'ggplot2', including splines, 1d and 2d densities, univariate average shifted histograms, a new map coordinate system based on the 'PROJ.4'-library along with geom_cartogram() that mimics the original functionality of geom_map(), formatters for "bytes", a stat_stepribbon() function, increased 'plotly' compatibility and the 'StateFace' open source font 'ProPublica'. Further new functionality includes lollipop charts, dumbbell charts, the ability to encircle points and coordinate-system-based text annotations.

Maintained by Bob Rudis. Last updated 2 years ago.

geom ggplot-extension ggplot2 ggplot2-geom ggplot2-scales

676 stars 12.60 score 2.3k scripts 7 dependents

inlabru-org

inlabru:Bayesian Latent Gaussian Modelling using INLA and Extensions

Facilitates spatial and general latent Gaussian modeling using integrated nested Laplace approximation via the INLA package (<https://www.r-inla.org>). Additionally, extends the GAM-like model class to more general nonlinear predictor expressions, and implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. Model components are specified with general inputs and mapping methods to the latent variables, and the predictors are specified via general R expressions, with separate expressions for each observation likelihood model in multi-likelihood models. A prediction method based on fast Monte Carlo sampling allows posterior prediction of general expressions of the latent variables. Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019) <doi:10.1111/2041-210X.13168>.

Maintained by Finn Lindgren. Last updated 1 hours ago.

96 stars 12.60 score 832 scripts 6 dependents

massimoaria

bibliometrix:Comprehensive Science Mapping Analysis

Tool for quantitative research in scientometrics and bibliometrics. It implements the comprehensive workflow for science mapping analysis proposed in Aria M. and Cuccurullo C. (2017) <doi:10.1016/j.joi.2017.08.007>. 'bibliometrix' provides various routines for importing bibliographic data from 'SCOPUS', 'Clarivate Analytics Web of Science' (<https://www.webofknowledge.com/>), 'Digital Science Dimensions' (<https://www.dimensions.ai/>), 'OpenAlex' (<https://openalex.org/>), 'Cochrane Library' (<https://www.cochranelibrary.com/>), 'Lens' (<https://lens.org>), and 'PubMed' (<https://pubmed.ncbi.nlm.nih.gov/>) databases, performing bibliometric analysis and building networks for co-citation, coupling, scientific collaboration and co-word analysis.

Maintained by Massimo Aria. Last updated 12 days ago.

bibliometric-analysis bibliometrics citation citation-network citations co-authors co-occurence co-word-analysis correspondence-analysis coupling isi-web journal manuscript quantitative-analysis scholars science science-mapping scientific scientometrics scopus

545 stars 12.54 score 518 scripts 2 dependents

billdenney

PKNCA:Perform Pharmacokinetic Non-Compartmental Analysis

Compute standard Non-Compartmental Analysis (NCA) parameters for typical pharmacokinetic analyses and summarize them.

Maintained by Bill Denney. Last updated 1 months ago.

nca noncompartmental-analysis pharmacokinetics

73 stars 12.53 score 214 scripts 4 dependents

aphalo

ggpp:Grammar Extensions to 'ggplot2'

Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Geometries: geom_table(), geom_plot() and geom_grob() add insets to plots using native data coordinates, while geom_table_npc(), geom_plot_npc() and geom_grob_npc() do the same using "npc" coordinates through new aesthetics "npcx" and "npcy". Statistics: select observations based on 2D density. Positions: radial nudging away from a center point and nudging away from a line or curve; combined stacking and nudging; combined dodging and nudging.

Maintained by Pedro J. Aphalo. Last updated 1 months ago.

data-labels dataviz ggplot2-enhancements ggplot2-geoms ggplot2-insets ggplot2-positions

129 stars 12.53 score 582 scripts 26 dependents

greta-dev

greta:Simple and Scalable Statistical Modelling in R

Write statistical models in R and fit them by MCMC and optimisation on CPUs and GPUs, using Google 'TensorFlow'. greta lets you write your own model like in BUGS, JAGS and Stan, except that you write models right in R, it scales well to massive datasets, and it’s easy to extend and build on. See the website for more information, including tutorials, examples, package documentation, and the greta forum.

Maintained by Nicholas Tierney. Last updated 20 days ago.

566 stars 12.53 score 396 scripts 6 dependents

bioc

microbiome:Microbiome Analytics

Utilities for microbiome analysis.

Maintained by Leo Lahti. Last updated 5 months ago.

metagenomics microbiome sequencing systemsbiology hitchip hitchip-atlas human-microbiome microbiology microbiome-analysis phyloseq population-study

293 stars 12.51 score 2.0k scripts 5 dependents

insightsengineering

tern:Create Common TLGs Used in Clinical Trials

Table, Listings, and Graphs (TLG) library for common outputs used in clinical trials.

Maintained by Joe Zhu. Last updated 2 months ago.

clinical-trials graphs listings nest outputs tables

83 stars 12.50 score 186 scripts 9 dependents

ropensci

treeio:Base Classes and Functions for Phylogenetic Tree Input and Output

'treeio' is an R package to make it easier to import and store phylogenetic tree with associated data; and to link external data from different sources to phylogeny. It also supports exporting phylogenetic tree with heterogeneous associated data to a single tree file and can be served as a platform for merging tree with associated data and converting file formats.

Maintained by Guangchuang Yu. Last updated 5 months ago.

software annotation clustering dataimport datarepresentation alignment multiplesequencealignment phylogenetics exporter parser phylogenetic-trees

102 stars 12.46 score 1.3k scripts 122 dependents

tidyverts

feasts:Feature Extraction and Statistics for Time Series

Provides a collection of features, decomposition methods, statistical summaries and graphics functions for the analysing tidy time series data. The package name 'feasts' is an acronym comprising of its key features: Feature Extraction And Statistics for Time Series.

Maintained by Mitchell OHara-Wild. Last updated 5 months ago.

300 stars 12.38 score 1.4k scripts 7 dependents

simongrund1

mitml:Tools for Multiple Imputation in Multilevel Modeling

Provides tools for multiple imputation of missing data in multilevel modeling. Includes a user-friendly interface to the packages 'pan' and 'jomo', and several functions for visualization, data management and the analysis of multiply imputed data sets.

Maintained by Simon Grund. Last updated 1 years ago.

imputation missing-data mixed-effects multilevel-data multilevel-models

29 stars 12.36 score 246 scripts 153 dependents

ouhscbbmc

REDCapR:Interaction Between R and REDCap

Encapsulates functions to streamline calls from R to the REDCap API. REDCap (Research Electronic Data CAPture) is a web application for building and managing online surveys and databases developed at Vanderbilt University. The Application Programming Interface (API) offers an avenue to access and modify data programmatically, improving the capacity for literate and reproducible programming.

Maintained by Will Beasley. Last updated 3 months ago.

redcap redcap-api

118 stars 12.36 score 438 scripts 6 dependents

asardaes

dtwclust:Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance

Time series clustering along with optimized techniques related to the Dynamic Time Warping distance and its corresponding lower bounds. Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole clustering are available. Functionality can be easily extended with custom distance measures and centroid definitions. Implementations of DTW barycenter averaging, a distance based on global alignment kernels, and the soft-DTW distance and centroid routines are also provided. All included distance functions have custom loops optimized for the calculation of cross-distance matrices, including parallelization support. Several cluster validity indices are included.

Maintained by Alexis Sarda. Last updated 8 months ago.

clustering dtw time-series openblas cpp

262 stars 12.35 score 406 scripts 14 dependents

ropensci

stplanr:Sustainable Transport Planning

Tools for transport planning with an emphasis on spatial transport data and non-motorized modes. The package was originally developed to support the 'Propensity to Cycle Tool', a publicly available strategic cycle network planning tool (Lovelace et al. 2017) <doi:10.5198/jtlu.2016.862>, but has since been extended to support public transport routing and accessibility analysis (Moreno-Monroy et al. 2017) <doi:10.1016/j.jtrangeo.2017.08.012> and routing with locally hosted routing engines such as 'OSRM' (Lowans et al. 2023) <doi:10.1016/j.enconman.2023.117337>. The main functions are for creating and manipulating geographic "desire lines" from origin-destination (OD) data (building on the 'od' package); calculating routes on the transport network locally and via interfaces to routing services such as <https://cyclestreets.net/> (Desjardins et al. 2021) <doi:10.1007/s11116-021-10197-1>; and calculating route segment attributes such as bearing. The package implements the 'travel flow aggregration' method described in Morgan and Lovelace (2020) <doi:10.1177/2399808320942779> and the 'OD jittering' method described in Lovelace et al. (2022) <doi:10.32866/001c.33873>. Further information on the package's aim and scope can be found in the vignettes and in a paper in the R Journal (Lovelace and Ellison 2018) <doi:10.32614/RJ-2018-053>, and in a paper outlining the landscape of open source software for geographic methods in transport planning (Lovelace, 2021) <doi:10.1007/s10109-020-00342-2>.

Maintained by Robin Lovelace. Last updated 7 months ago.

cycle cycling desire-lines origin-destination peer-reviewed pubic-transport route-network routes routing spatial transport transport-planning transportation walking

427 stars 12.31 score 684 scripts 3 dependents

gaospecial

ggVennDiagram:A 'ggplot2' Implement of Venn Diagram

Easy-to-use functions to generate 2-7 sets Venn or upset plot in publication quality. 'ggVennDiagram' plot Venn or upset using well-defined geometry dataset and 'ggplot2'. The shapes of 2-4 sets Venn use circles and ellipses, while the shapes of 4-7 sets Venn use irregular polygons (4 has both forms), which are developed and imported from another package 'venn', authored by Adrian Dusa. We provided internal functions to integrate shape data with user provided sets data, and calculated the geometry of every regions/intersections of them, then separately plot Venn in four components, set edges/labels, and region edges/labels. From version 1.0, it is possible to customize these components as you demand in ordinary 'ggplot2' grammar. From version 1.4.4, it supports unlimited number of sets, as it can draw a plain upset plot automatically when number of sets is more than 7.

Maintained by Chun-Hui Gao. Last updated 5 months ago.

set-operations upset upsetplot venn-diagram venn-plot

292 stars 12.31 score 1.3k scripts 4 dependents

bioc

ReactomePA:Reactome Pathway Analysis

This package provides functions for pathway analysis based on REACTOME pathway database. It implements enrichment analysis, gene set enrichment analysis and several functions for visualization. This package is not affiliated with the Reactome team.

Maintained by Guangchuang Yu. Last updated 5 months ago.

pathways visualization annotation multiplecomparison genesetenrichment reactome enrichment-analysis reactome-pathway-analysis reactomepa

40 stars 12.25 score 1.5k scripts 7 dependents

yulab-smu

aplot:Decorate a 'ggplot' with Associated Information

For many times, we are not just aligning plots as what 'cowplot' and 'patchwork' did. Users would like to align associated information that requires axes to be exactly matched in subplots, e.g. hierarchical clustering with a heatmap. Inspired by the 'Method 2' in 'ggtree' (G Yu (2018) <doi:10.1093/molbev/msy194>), 'aplot' provides utilities to aligns associated subplots to a main plot at different sides (left, right, top and bottom) with axes exactly matched.

Maintained by Guangchuang Yu. Last updated 1 months ago.

103 stars 12.25 score 520 scripts 118 dependents

bioc

ggbio:Visualization tools for genomic data

The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.

Maintained by Michael Lawrence. Last updated 5 months ago.

infrastructure visualization

111 stars 12.23 score 734 scripts 16 dependents

markmfredrickson

optmatch:Functions for Optimal Matching

Distance based bipartite matching using minimum cost flow, oriented to matching of treatment and control groups in observational studies ('Hansen' and 'Klopfer' 2006 <doi:10.1198/106186006X137047>). Routines are provided to generate distances from generalised linear models (propensity score matching), formulas giving variables on which to limit matched distances, stratified or exact matching directives, or calipers, alone or in combination.

Maintained by Josh Errickson. Last updated 4 months ago.

matching openblas cpp

47 stars 12.22 score 588 scripts 5 dependents

igordot

msigdbr:MSigDB Gene Sets for Multiple Organisms in a Tidy Data Format

Provides the 'Molecular Signatures Database' (MSigDB) gene sets typically used with the 'Gene Set Enrichment Analysis' (GSEA) software (Subramanian et al. 2005 <doi:10.1073/pnas.0506580102>, Liberzon et al. 2015 <doi:10.1016/j.cels.2015.12.004>, Castanza et al. 2023 <doi:10.1038/s41592-023-02014-7>) as an R data frame. The package includes the human genes as listed in MSigDB as well as the corresponding symbols and IDs for frequently studied model organisms such as mouse, rat, pig, fly, and yeast.

Maintained by Igor Dolgalev. Last updated 12 days ago.

enrichment-analysis gene-sets genomics gsea msigdb pathway-analysis pathways

73 stars 12.20 score 3.6k scripts 20 dependents

rsquaredacademy

olsrr:Tools for Building OLS Regression Models

Tools designed to make it easier for users, particularly beginner/intermediate R users to build ordinary least squares regression models. Includes comprehensive regression output, heteroskedasticity tests, collinearity diagnostics, residual diagnostics, measures of influence, model fit assessment and variable selection procedures.

Maintained by Aravind Hebbali. Last updated 5 months ago.

collinearity-diagnostics linear-models regression stepwise-regression

103 stars 12.19 score 1.4k scripts 4 dependents

stuart-lab

Signac:Analysis of Single-Cell Chromatin Data

A framework for the analysis and exploration of single-cell chromatin data. The 'Signac' package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis. Reference: Stuart et al. (2021) <doi:10.1038/s41592-021-01282-5>.

Maintained by Tim Stuart. Last updated 7 months ago.

atac bioinformatics single-cell zlib cpp

355 stars 12.18 score 3.7k scripts 1 dependents

tidyverts

fabletools:Core Tools for Packages in the 'fable' Framework

Provides tools, helpers and data structures for developing models and time series functions for 'fable' and extension packages. These tools support a consistent and tidy interface for time series modelling and analysis.

Maintained by Mitchell OHara-Wild. Last updated 2 months ago.

91 stars 12.18 score 396 scripts 18 dependents

bcallaway11

did:Treatment Effects with Multiple Periods and Groups

The standard Difference-in-Differences (DID) setup involves two periods and two groups -- a treated group and untreated group. Many applications of DID methods involve more than two periods and have individuals that are treated at different points in time. This package contains tools for computing average treatment effect parameters in Difference in Differences setups with more than two periods and with variation in treatment timing using the methods developed in Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>. The main parameters are group-time average treatment effects which are the average treatment effect for a particular group at a a particular time. These can be aggregated into a fewer number of treatment effect parameters, and the package deals with the cases where there is selective treatment timing, dynamic treatment effects, calendar time effects, or combinations of these. There are also functions for testing the Difference in Differences assumption, and plotting group-time average treatment effects.

Maintained by Brantly Callaway. Last updated 5 days ago.

329 stars 12.09 score 696 scripts 3 dependents

tidymodels

probably:Tools for Post-Processing Predicted Values

Models can be improved by post-processing class probabilities, by: recalibration, conversion to hard probabilities, assessment of equivocal zones, and other activities. 'probably' contains tools for conducting these operations as well as calibration tools and conformal inference techniques for regression models.

Maintained by Max Kuhn. Last updated 6 months ago.

115 stars 12.09 score 21k scripts 1 dependents

mrc-ide

EpiEstim:Estimate Time Varying Reproduction Numbers from Epidemic Curves

Tools to quantify transmissibility throughout an epidemic from the analysis of time series of incidence as described in Cori et al. (2013) <doi:10.1093/aje/kwt133> and Wallinga and Teunis (2004) <doi:10.1093/aje/kwh255>.

Maintained by Anne Cori. Last updated 7 months ago.

95 stars 12.06 score 1.0k scripts 7 dependents

tidymodels

workflowsets:Create a Collection of 'tidymodels' Workflows

A workflow is a combination of a model and preprocessors (e.g, a formula, recipe, etc.) (Kuhn and Silge (2021) <https://www.tmwr.org/>). In order to try different combinations of these, an object can be created that contains many workflows. There are functions to create workflows en masse as well as training them and visualizing the results.

Maintained by Simon Couch. Last updated 5 months ago.

94 stars 12.04 score 294 scripts 19 dependents

dreamrs

datamods:Modules to Import and Manipulate Data in 'Shiny'

'Shiny' modules to import data into an application or 'addin' from various sources, and to manipulate them after that.

Maintained by Victor Perrier. Last updated 26 days ago.

shiny shiny-modules

144 stars 12.03 score 174 scripts 7 dependents

crsh

papaja:Prepare American Psychological Association Journal Articles with R Markdown

Tools to create dynamic, submission-ready manuscripts, which conform to American Psychological Association manuscript guidelines. We provide R Markdown document formats for manuscripts (PDF and Word) and revision letters (PDF). Helper functions facilitate reporting statistical analyses or create publication-ready tables and plots.

Maintained by Frederik Aust. Last updated 1 months ago.

apa apa-guidelines journal manuscript psychology reproducible-paper reproducible-research rmarkdown

663 stars 12.00 score 1.7k scripts 2 dependents

cdalzell

Lahman:Sean 'Lahman' Baseball Database

Provides the tables from the 'Sean Lahman Baseball Database' as a set of R data.frames. It uses the data on pitching, hitting and fielding performance and other tables from 1871 through 2023, as recorded in the 2024 version of the database. Documentation examples show how many baseball questions can be investigated.

Maintained by Chris Dalzell. Last updated 4 months ago.

79 stars 12.00 score 1.7k scripts 2 dependents

zachmayer

caretEnsemble:Ensembles of Caret Models

Functions for creating ensembles of caret models: caretList() and caretStack(). caretList() is a convenience function for fitting multiple caret::train() models to the same dataset. caretStack() will make linear or non-linear combinations of these models, using a caret::train() model as a meta-model.

Maintained by Zachary A. Deane-Mayer. Last updated 3 months ago.

226 stars 11.98 score 780 scripts 1 dependents

bioc

ExperimentHub:Client to access ExperimentHub resources

This package provides a client for the Bioconductor ExperimentHub web resource. ExperimentHub provides a central location where curated data from experiments, publications or training courses can be accessed. Each resource has associated metadata, tags and date of modification. The client creates and manages a local cache of files retrieved enabling quick and reproducible access.

Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.

infrastructure dataimport gui thirdpartyclient core-package u24ca289073

10 stars 11.94 score 764 scripts 57 dependents

bioc

GenomicDataCommons:NIH / NCI Genomic Data Commons Access

Programmatically access the NIH / NCI Genomic Data Commons RESTful service.

Maintained by Sean Davis. Last updated 2 months ago.

dataimport sequencing api-client bioconductor bioinformatics cancer core-services data-science genomics nci tcga vignette

87 stars 11.94 score 238 scripts 12 dependents

jinghuazhao

gap:Genetic Analysis Package

As first reported [Zhao, J. H. 2007. "gap: Genetic Analysis Package". J Stat Soft 23(8):1-18. <doi:10.18637/jss.v023.i08>], it is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).

Maintained by Jing Hua Zhao. Last updated 6 days ago.

genetics imputation lmm fortran

12 stars 11.94 score 448 scripts 16 dependents

xfim

ggmcmc:Tools for Analyzing MCMC Simulations from Bayesian Inference

Tools for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis. The package also facilitates the graphical interpretation of models by providing flexible functions to plot the results against observed variables, and functions to work with hierarchical/multilevel batches of parameters (Fernández-i-Marín, 2016 <doi:10.18637/jss.v070.i09>).

Maintained by Xavier Fernández i Marín. Last updated 2 years ago.

bayesian-data-analysis ggplot2 graphical jags mcmc stan

111 stars 11.94 score 1.6k scripts 8 dependents

pecanproject

PEcAn.DB:PEcAn Functions Used for Ecological Forecasts and Reanalysis

The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.

Maintained by David LeBauer. Last updated 9 hours ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants

216 stars 11.91 score 127 scripts 27 dependents

bioc

QFeatures:Quantitative features for mass spectrometry data

The QFeatures infrastructure enables the management and processing of quantitative features for high-throughput mass spectrometry assays. It provides a familiar Bioconductor user experience to manages quantitative data across different assay levels (such as peptide spectrum matches, peptides and proteins) in a coherent and tractable format.

Maintained by Laurent Gatto. Last updated 27 days ago.

infrastructure massspectrometry proteomics metabolomics bioconductor mass-spectrometry

27 stars 11.87 score 278 scripts 49 dependents

hannameyer

CAST:'caret' Applications for Spatial-Temporal Models

Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. CAST includes functions to improve spatial or spatial-temporal modelling tasks using 'caret'. It includes the newly suggested 'Nearest neighbor distance matching' cross-validation to estimate the performance of spatial prediction models and allows for spatial variable selection to selects suitable predictor variables in view to their contribution to the spatial model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models. Methods are described in Meyer et al. (2018) <doi:10.1016/j.envsoft.2017.12.001>; Meyer et al. (2019) <doi:10.1016/j.ecolmodel.2019.108815>; Meyer and Pebesma (2021) <doi:10.1111/2041-210X.13650>; Milà et al. (2022) <doi:10.1111/2041-210X.13851>; Meyer and Pebesma (2022) <doi:10.1038/s41467-022-29838-9>; Linnenbrink et al. (2023) <doi:10.5194/egusphere-2023-1308>; Schumacher et al. (2024) <doi:10.5194/egusphere-2024-2730>. The package is described in detail in Meyer et al. (2024) <doi:10.48550/arXiv.2404.06978>.

Maintained by Hanna Meyer. Last updated 2 months ago.

autocorrelation caret feature-selection machine-learning overfitting predictive-modeling spatial spatio-temporal variable-selection

114 stars 11.85 score 298 scripts 1 dependents

guido-s

netmeta:Network Meta-Analysis using Frequentist Methods

A comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) <doi:10.18637/jss.v106.i02> and supporting Schwarzer et al. (2015) <doi:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <doi:10.1002/jrsm.1058>; - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <doi:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <doi:10.1002/sim.8158>, or penalised logistic regression (Evrenoglou et al., 2022) <doi:10.1002/sim.9562>; - rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) <doi:10.1016/j.jclinepi.2010.03.016>; - ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to Rücker & Schwarzer (2015) <doi:10.1186/s12874-015-0060-8>; - split direct and indirect evidence to check consistency (Dias et al., 2010) <doi:10.1002/sim.3767>, (Efthimiou et al., 2019) <doi:10.1002/sim.8158>; - league table with network meta-analysis results; - 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) <doi:10.1002/jrsm.57>; - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <doi:10.1186/1471-2288-13-35>; - measures characterizing the flow of evidence between two treatments by König et al. (2013) <doi:10.1002/sim.6001>; - automated drawing of network graphs described in Rücker & Schwarzer (2016) <doi:10.1002/jrsm.1143>; - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) <doi:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <doi:10.1002/jrsm.1270>; - contribution matrix as described in Papakonstantinou et al. (2018) <doi:10.12688/f1000research.14770.3> and Davies et al. (2022) <doi:10.1002/sim.9346>; - subgroup network meta-analysis.

Maintained by Guido Schwarzer. Last updated 10 days ago.

meta-analysis network-meta-analysis rstudio

33 stars 11.84 score 199 scripts 10 dependents

rstudio

tfruns:Training Run Tools for 'TensorFlow'

Create and manage unique directories for each 'TensorFlow' training run. Provides a unique, time stamped directory for each run along with functions to retrieve the directory of the latest run or latest several runs.

Maintained by Tomasz Kalinowski. Last updated 12 months ago.

34 stars 11.80 score 325 scripts 77 dependents

guangchuangyu

hexSticker:Create Hexagon Sticker in R

Helper functions for creating reproducible hexagon sticker purely in R.

Maintained by Guangchuang Yu. Last updated 2 months ago.

ggplot2 hexagon-sticker logo stickers visualization

773 stars 11.79 score 1.3k scripts 8 dependents

r-causal

ggdag:Analyze and Create Elegant Directed Acyclic Graphs

Tidy, analyze, and plot directed acyclic graphs (DAGs). 'ggdag' is built on top of 'dagitty', an R package that uses the 'DAGitty' web tool (<https://dagitty.net/>) for creating and analyzing DAGs. 'ggdag' makes it easy to tidy and plot 'dagitty' objects using 'ggplot2' and 'ggraph', as well as common analytic and graphical functions, such as determining adjustment sets and node relationships.

Maintained by Malcolm Barrett. Last updated 8 months ago.

causal-inference dag ggplot-extension

443 stars 11.78 score 1.8k scripts 5 dependents

friendly

heplots:Visualizing Hypothesis Tests in Multivariate Linear Models

Provides HE plot and other functions for visualizing hypothesis tests in multivariate linear models. HE plots represent sums-of-squares-and-products matrices for linear hypotheses and for error using ellipses (in two dimensions) and ellipsoids (in three dimensions). The related 'candisc' package provides visualizations in a reduced-rank canonical discriminant space when there are more than a few response variables.

Maintained by Michael Friendly. Last updated 8 days ago.

linear-hypotheses matrices multivariate-linear-models plot repeated-measure-designs visualizing-hypothesis-tests

9 stars 11.78 score 1.1k scripts 7 dependents

datalorax

equatiomatic:Transform Models into 'LaTeX' Equations

The goal of 'equatiomatic' is to reduce the pain associated with writing 'LaTeX' formulas from fitted models. The primary function of the package, extract_eq(), takes a fitted model object as its input and returns the corresponding 'LaTeX' code for the model.

Maintained by Philippe Grosjean. Last updated 22 days ago.

619 stars 11.75 score 424 scripts 5 dependents

bioc

variancePartition:Quantify and interpret drivers of variation in multilevel gene expression experiments

Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. Includes dream differential expression analysis for repeated measures.

Maintained by Gabriel E. Hoffman. Last updated 3 months ago.

rnaseq geneexpression genesetenrichment differentialexpression batcheffect qualitycontrol regression epigenetics functionalgenomics transcriptomics normalization preprocessing microarray immunooncology software

7 stars 11.69 score 1.1k scripts 3 dependents

jthomasmock

gtExtras:Extending 'gt' for Beautiful HTML Tables

Provides additional functions for creating beautiful tables with 'gt'. The functions are generally wrappers around boilerplate or adding opinionated niche capabilities and helpers functions.

Maintained by Thomas Mock. Last updated 12 months ago.

data-science data-visualization datascience ggplot2 gt plots sparkline sparkline-graphs sparklines tables

201 stars 11.66 score 2.4k scripts 5 dependents

mrkaye97

slackr:Send Messages, Images, R Objects and Files to 'Slack' Channels/Users

'Slack' <https://slack.com/> provides a service for teams to collaborate by sharing messages, images, links, files and more. Functions are provided that make it possible to interact with the 'Slack' platform 'API'. When you need to share information or data from R, rather than resort to copy/ paste in e-mails or other services like 'Skype' <https://www.skype.com/en/>, you can use this package to send well-formatted output from multiple R objects and expressions to all teammates at the same time with little effort. You can also send images from the current graphics device, R objects, and upload files.

Maintained by Matt Kaye. Last updated 6 months ago.

slack

306 stars 11.66 score 179 scripts

yutannihilation

gghighlight:Highlight Lines and Points in 'ggplot2'

Make it easier to explore data with highlights.

Maintained by Hiroaki Yutani. Last updated 7 months ago.

523 stars 11.64 score 1.6k scripts 4 dependents

ateucher

rmapshaper:Client for 'mapshaper' for 'Geospatial' Operations

Edit and simplify 'geojson', 'Spatial', and 'sf' objects. This is wrapper around the 'mapshaper' 'JavaScript' library by Matthew Bloch <https://github.com/mbloch/mapshaper/> to perform topologically-aware polygon simplification, as well as other operations such as clipping, erasing, dissolving, and converting 'multi-part' to 'single-part' geometries.

Maintained by Andy Teucher. Last updated 9 months ago.

rlang

204 stars 11.64 score 2.1k scripts 18 dependents

haleyjeppson

ggmosaic:Mosaic Plots in the 'ggplot2' Framework

Mosaic plots in the 'ggplot2' framework. Mosaic plot functionality is provided in a single 'ggplot2' layer by calling the geom 'mosaic'.

Maintained by Haley Jeppson. Last updated 6 months ago.

167 stars 11.63 score 1.8k scripts 4 dependents

pecanproject

PEcAn.data.atmosphere:PEcAn Functions Used for Managing Climate Driver Data

The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The PECAn.data.atmosphere package converts climate driver data into a standard format for models integrated into PEcAn. As a standalone package, it provides an interface to access diverse climate data sets.

Maintained by David LeBauer. Last updated 9 hours ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants

216 stars 11.63 score 64 scripts 14 dependents

koalaverse

vip:Variable Importance Plots

A general framework for constructing variable importance plots from various types of machine learning models in R. Aside from some standard model- specific variable importance measures, this package also provides model- agnostic approaches that can be applied to any supervised learning algorithm. These include 1) an efficient permutation-based variable importance measure, 2) variable importance based on Shapley values (Strumbelj and Kononenko, 2014) <doi:10.1007/s10115-013-0679-x>, and 3) the variance-based approach described in Greenwell et al. (2018) <arXiv:1805.04755>. A variance-based method for quantifying the relative strength of interaction effects is also included (see the previous reference for details).

Maintained by Brandon M. Greenwell. Last updated 2 years ago.

interaction-effect machine-learning partial-dependence-plot supervised-learning-algorithms variable-importance variable-importance-plots

187 stars 11.61 score 3.5k scripts 6 dependents

ggseg

ggseg:Plotting Tool for Brain Atlases

Contains 'ggplot2' geom for plotting brain atlases using simple features. The largest component of the package is the data for the two built-in atlases. Mowinckel & Vidal-Piñeiro (2020) <doi:10.1177/2515245920928009>.

Maintained by Athanasia Mo Mowinckel. Last updated 2 years ago.

221 stars 11.57 score 590 scripts 14 dependents

edwinth

padr:Quickly Get Datetime Data Ready for Analysis

Transforms datetime data into a format ready for analysis. It offers two core functionalities; aggregating data to a higher level interval (thicken) and imputing records where observations were absent (pad).

Maintained by Edwin Thoen. Last updated 4 months ago.

cpp

132 stars 11.55 score 428 scripts 20 dependents

projectmosaic

ggformula:Formula Interface to the Grammar of Graphics

Provides a formula interface to 'ggplot2' graphics.

Maintained by Randall Pruim. Last updated 1 years ago.

38 stars 11.55 score 1.7k scripts 25 dependents

bioc

mia:Microbiome analysis

mia implements tools for microbiome analysis based on the SummarizedExperiment, SingleCellExperiment and TreeSummarizedExperiment infrastructure. Data wrangling and analysis in the context of taxonomic data is the main scope. Additional functions for common task are implemented such as community indices calculation and summarization.

Maintained by Tuomas Borman. Last updated 4 days ago.

microbiome software dataimport analysis bioconductor cpp

51 stars 11.51 score 316 scripts 5 dependents

ropensci

drake:A Pipeline Toolkit for Reproducible Computation at Scale

A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, there is native support for parallel and distributed computing, and completed projects have tangible evidence that they are reproducible. Extensive documentation, from beginner-friendly tutorials to practical examples and more, is available at the reference website <https://docs.ropensci.org/drake/> and the online manual <https://books.ropensci.org/drake/>.

Maintained by William Michael Landau. Last updated 4 months ago.

data-science drake high-performance-computing makefile peer-reviewed pipeline reproducibility reproducible-research ropensci workflow

1.3k stars 11.49 score 1.7k scripts 1 dependents

tidymodels

stacks:Tidy Model Stacking

Model stacking is an ensemble technique that involves training a model to combine the outputs of many diverse statistical models, and has been shown to improve predictive performance in a variety of settings. 'stacks' implements a grammar for 'tidymodels'-aligned model stacking.

Maintained by Simon Couch. Last updated 5 months ago.

298 stars 11.46 score 840 scripts

johncoene

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

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

Maintained by David Munoz Tord. Last updated 18 days ago.

echarts hacktoberfest htmlwidget htmlwidgets visualization

603 stars 11.45 score 1.3k scripts 11 dependents

larmarange

broom.helpers:Helpers for Model Coefficients Tibbles

Provides suite of functions to work with regression model 'broom::tidy()' tibbles. The suite includes functions to group regression model terms by variable, insert reference and header rows for categorical variables, add variable labels, and more.

Maintained by Joseph Larmarange. Last updated 25 days ago.

22 stars 11.45 score 165 scripts 2 dependents

bioc

destiny:Creates diffusion maps

Create and plot diffusion maps.

Maintained by Philipp Angerer. Last updated 4 months ago.

cellbiology cellbasedassays clustering software visualization diffusion-maps dimensionality-reduction cpp

82 stars 11.44 score 792 scripts 1 dependents

ewenharrison

finalfit:Quickly Create Elegant Regression Results Tables and Plots when Modelling

Generate regression results tables and plots in final format for publication. Explore models and export directly to PDF and 'Word' using 'RMarkdown'.

Maintained by Ewen Harrison. Last updated 10 days ago.

270 stars 11.43 score 1.0k scripts

darwin-eu

CDMConnector:Connect to an OMOP Common Data Model

Provides tools for working with observational health data in the Observational Medical Outcomes Partnership (OMOP) Common Data Model format with a pipe friendly syntax. Common data model database table references are stored in a single compound object along with metadata.

Maintained by Adam Black. Last updated 1 months ago.

12 stars 11.43 score 502 scripts 12 dependents

epimodel

EpiModel:Mathematical Modeling of Infectious Disease Dynamics

Tools for simulating mathematical models of infectious disease dynamics. Epidemic model classes include deterministic compartmental models, stochastic individual-contact models, and stochastic network models. Network models use the robust statistical methods of exponential-family random graph models (ERGMs) from the Statnet suite of software packages in R. Standard templates for epidemic modeling include SI, SIR, and SIS disease types. EpiModel features an API for extending these templates to address novel scientific research aims. Full methods for EpiModel are detailed in Jenness et al. (2018, <doi:10.18637/jss.v084.i08>).

Maintained by Samuel Jenness. Last updated 2 months ago.

agent-based-modeling epidemics epidemiology infectious-diseases network-graph cpp

250 stars 11.43 score 315 scripts

luukvdmeer

sfnetworks:Tidy Geospatial Networks

Provides a tidy approach to spatial network analysis, in the form of classes and functions that enable a seamless interaction between the network analysis package 'tidygraph' and the spatial analysis package 'sf'.

Maintained by Lucas van der Meer. Last updated 3 months ago.

geospatial-networks network-analysis rspatial simple-features spatial-analysis spatial-data-science spatial-networks tidygraph tidyverse

373 stars 11.43 score 332 scripts 7 dependents

jacob-long

interactions:Comprehensive, User-Friendly Toolkit for Probing Interactions

A suite of functions for conducting and interpreting analysis of statistical interaction in regression models that was formerly part of the 'jtools' package. Functionality includes visualization of two- and three-way interactions among continuous and/or categorical variables as well as calculation of "simple slopes" and Johnson-Neyman intervals (see e.g., Bauer & Curran, 2005 <doi:10.1207/s15327906mbr4003_5>). These capabilities are implemented for generalized linear models in addition to the standard linear regression context.

Maintained by Jacob A. Long. Last updated 8 months ago.

interactions moderation social-sciences statistics

131 stars 11.40 score 1.2k scripts 5 dependents

lazappi

clustree:Visualise Clusterings at Different Resolutions

Deciding what resolution to use can be a difficult question when approaching a clustering analysis. One way to approach this problem is to look at how samples move as the number of clusters increases. This package allows you to produce clustering trees, a visualisation for interrogating clusterings as resolution increases.

Maintained by Luke Zappia. Last updated 1 years ago.

clustering clustering-trees visualisation visualization

219 stars 11.40 score 1.9k scripts 5 dependents

insightsengineering

cards:Analysis Results Data

Construct CDISC (Clinical Data Interchange Standards Consortium) compliant Analysis Results Data objects. These objects are used and re-used to construct summary tables, visualizations, and written reports. The package also exports utilities for working with these objects and creating new Analysis Results Data objects.

Maintained by Daniel D. Sjoberg. Last updated 30 days ago.

analysis cdisc dataset

40 stars 11.40 score 100 scripts 19 dependents

markfairbanks

tidytable:Tidy Interface to 'data.table'

A tidy interface to 'data.table', giving users the speed of 'data.table' while using tidyverse-like syntax.

Maintained by Mark Fairbanks. Last updated 2 months ago.

460 stars 11.39 score 732 scripts 11 dependents

ropensci

assertr:Assertive Programming for R Analysis Pipelines

Provides functionality to assert conditions that have to be met so that errors in data used in analysis pipelines can fail quickly. Similar to 'stopifnot()' but more powerful, friendly, and easier for use in pipelines.

Maintained by Tony Fischetti. Last updated 12 months ago.

analysis-pipeline assertion-library assertion-methods assertions peer-reviewed predicate-functions

478 stars 11.39 score 452 scripts 12 dependents

openintrostat

openintro:Datasets and Supplemental Functions from 'OpenIntro' Textbooks and Labs

Supplemental functions and data for 'OpenIntro' resources, which includes open-source textbooks and resources for introductory statistics (<https://www.openintro.org/>). The package contains datasets used in our open-source textbooks along with custom plotting functions for reproducing book figures. Note that many functions and examples include color transparency; some plotting elements may not show up properly (or at all) when run in some versions of Windows operating system.

Maintained by Mine Çetinkaya-Rundel. Last updated 3 months ago.

data openintro

240 stars 11.39 score 6.0k scripts