R-universe search: needs:scales

tidyverse

ggplot2:Create Elegant Data Visualisations Using the Grammar of Graphics

A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.

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

data-visualisation visualisation

6.6k stars 25.10 score 645k scripts 7.6k 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

thomasp85

patchwork:The Composer of Plots

The 'ggplot2' package provides a strong API for sequentially building up a plot, but does not concern itself with composition of multiple plots. 'patchwork' is a package that expands the API to allow for arbitrarily complex composition of plots by, among others, providing mathematical operators for combining multiple plots. Other packages that try to address this need (but with a different approach) are 'gridExtra' and 'cowplot'.

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

ggplot-extension ggplot2 visualization

2.5k stars 19.83 score 82k scripts 657 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

haozhu233

kableExtra:Construct Complex Table with 'kable' and Pipe Syntax

Build complex HTML or 'LaTeX' tables using 'kable()' from 'knitr' and the piping syntax from 'magrittr'. Function 'kable()' is a light weight table generator coming from 'knitr'. This package simplifies the way to manipulate the HTML or 'LaTeX' codes generated by 'kable()' and allows users to construct complex tables and customize styles using a readable syntax.

Maintained by Hao Zhu. Last updated 25 days ago.

html kable kableextra knitr latex rmarkdown

702 stars 19.35 score 55k scripts 163 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

slowkow

ggrepel:Automatically Position Non-Overlapping Text Labels with 'ggplot2'

Provides text and label geoms for 'ggplot2' that help to avoid overlapping text labels. Labels repel away from each other and away from the data points.

Maintained by Kamil Slowikowski. Last updated 5 months ago.

ggplot2 text visualization cpp

1.2k stars 19.20 score 37k scripts 1.2k dependents

stan-dev

rstan:R Interface to Stan

User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.

Maintained by Ben Goodrich. Last updated 3 days ago.

bayesian-data-analysis bayesian-inference bayesian-statistics mcmc stan cpp

1.1k stars 18.86 score 14k scripts 281 dependents

wilkelab

cowplot:Streamlined Plot Theme and Plot Annotations for 'ggplot2'

Provides various features that help with creating publication-quality figures with 'ggplot2', such as a set of themes, functions to align plots and arrange them into complex compound figures, and functions that make it easy to annotate plots and or mix plots with images. The package was originally written for internal use in the Wilke lab, hence the name (Claus O. Wilke's plot package). It has also been used extensively in the book Fundamentals of Data Visualization.

Maintained by Claus O. Wilke. Last updated 3 months ago.

714 stars 18.83 score 75k scripts 1.4k 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

nanxstats

ggsci:Scientific Journal and Sci-Fi Themed Color Palettes for 'ggplot2'

A collection of 'ggplot2' color palettes inspired by plots in scientific journals, data visualization libraries, science fiction movies, and TV shows.

Maintained by Nan Xiao. Last updated 10 months ago.

color-palettes data-visualization ggplot2 ggsci sci-fi scientific-journals visualization

680 stars 18.00 score 26k scripts 438 dependents

sjmgarnier

viridis:Colorblind-Friendly Color Maps for R

Color maps designed to improve graph readability for readers with common forms of color blindness and/or color vision deficiency. The color maps are also perceptually-uniform, both in regular form and also when converted to black-and-white for printing. This package also contains 'ggplot2' bindings for discrete and continuous color and fill scales. A lean version of the package called 'viridisLite' that does not include the 'ggplot2' bindings can be found at <https://cran.r-project.org/package=viridisLite>.

Maintained by Simon Garnier. Last updated 1 years ago.

color-blindness color-scheme

298 stars 17.96 score 49k scripts 1.2k dependents

harrelfe

Hmisc:Harrell Miscellaneous

Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, simulation, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis.

Maintained by Frank E Harrell Jr. Last updated 6 days ago.

fortran

209 stars 17.64 score 17k scripts 750 dependents

robjhyndman

forecast:Forecasting Functions for Time Series and Linear Models

Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.

Maintained by Rob Hyndman. Last updated 7 months ago.

forecast forecasting openblas cpp

1.1k stars 17.46 score 16k scripts 240 dependents

rstudio

leaflet:Create Interactive Web Maps with the JavaScript 'Leaflet' Library

Create and customize interactive maps using the 'Leaflet' JavaScript library and the 'htmlwidgets' package. These maps can be used directly from the R console, from 'RStudio', in Shiny applications and R Markdown documents.

Maintained by Joe Cheng. Last updated 28 days ago.

gis leaflet-map spatial

821 stars 17.20 score 39k scripts 178 dependents

talgalili

dendextend:Extending 'dendrogram' Functionality in R

Offers a set of functions for extending 'dendrogram' objects in R, letting you visualize and compare trees of 'hierarchical clusterings'. You can (1) Adjust a tree's graphical parameters - the color, size, type, etc of its branches, nodes and labels. (2) Visually and statistically compare different 'dendrograms' to one another.

Maintained by Tal Galili. Last updated 2 months ago.

154 stars 17.13 score 6.0k scripts 165 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

const-ae

ggsignif:Significance Brackets for 'ggplot2'

Enrich your 'ggplots' with group-wise comparisons. This package provides an easy way to indicate if two groups are significantly different. Commonly this is shown by a bracket on top connecting the groups of interest which itself is annotated with the level of significance (NS, *, **, ***). The package provides a single layer (geom_signif()) that takes the groups for comparison and the test (t.test(), wilcox.text() etc.) as arguments and adds the annotation to the plot.

Maintained by Constantin Ahlmann-Eltze. Last updated 8 months ago.

asterisk ggplot-extension ggplot2 significance-stars

601 stars 16.89 score 3.6k scripts 417 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

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

wilkelab

ggridges:Ridgeline Plots in 'ggplot2'

Ridgeline plots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in 'ggplot2'.

Maintained by Claus O. Wilke. Last updated 4 months ago.

418 stars 16.71 score 14k scripts 285 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 5 hours ago.

bayesian-inference brms multilevel-models stan statistical-models

1.3k stars 16.64 score 13k scripts 35 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

mlverse

torch:Tensors and Neural Networks with 'GPU' Acceleration

Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <doi:10.48550/arXiv.1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.

Maintained by Daniel Falbel. Last updated 5 days ago.

autograd deep-learning torch cpp

521 stars 16.50 score 1.4k scripts 39 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

bioc

fgsea:Fast Gene Set Enrichment Analysis

The package implements an algorithm for fast gene set enrichment analysis. Using the fast algorithm allows to make more permutations and get more fine grained p-values, which allows to use accurate stantard approaches to multiple hypothesis correction.

Maintained by Alexey Sergushichev. Last updated 12 days ago.

geneexpression differentialexpression genesetenrichment pathways cpp

392 stars 16.31 score 3.9k scripts 101 dependents

r-tmap

tmap:Thematic Maps

Thematic maps are geographical maps in which spatial data distributions are visualized. This package offers a flexible, layer-based, and easy to use approach to create thematic maps, such as choropleths and bubble maps.

Maintained by Martijn Tennekes. Last updated 3 days ago.

choropleth-maps maps spatial thematic-maps visualisation

879 stars 16.25 score 13k scripts 24 dependents

jrnold

ggthemes:Extra Themes, Scales and Geoms for 'ggplot2'

Some extra themes, geoms, and scales for 'ggplot2'. Provides 'ggplot2' themes and scales that replicate the look of plots by Edward Tufte, Stephen Few, 'Fivethirtyeight', 'The Economist', 'Stata', 'Excel', and 'The Wall Street Journal', among others. Provides 'geoms' for Tufte's box plot and range frame.

Maintained by Jeffrey B. Arnold. Last updated 1 years ago.

data-visualisation ggplot2 ggplot2-themes plot plotting theme visualization

1.3k stars 16.17 score 40k scripts 102 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

bioc

DESeq2:Differential gene expression analysis based on the negative binomial distribution

Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

Maintained by Michael Love. Last updated 26 days ago.

sequencing rnaseq chipseq geneexpression transcription normalization differentialexpression bayesian regression principalcomponent clustering immunooncology openblas cpp

375 stars 16.11 score 17k scripts 115 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

wilkelab

ggtext:Improved Text Rendering Support for 'ggplot2'

A 'ggplot2' extension that enables the rendering of complex formatted plot labels (titles, subtitles, facet labels, axis labels, etc.). Text boxes with automatic word wrap are also supported.

Maintained by Brenton M. Wiernik. Last updated 3 years ago.

657 stars 15.71 score 13k scripts 155 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 19 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

thomasp85

gganimate:A Grammar of Animated Graphics

The grammar of graphics as implemented in the 'ggplot2' package has been successful in providing a powerful API for creating static visualisation. In order to extend the API for animated graphics this package provides a completely new set of grammar, fully compatible with 'ggplot2' for specifying transitions and animations in a flexible and extensible way.

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

animation data-visualization ggplot-extension ggplot2 transition

2.0k stars 15.53 score 13k scripts 24 dependents

eclarke

ggbeeswarm:Categorical Scatter (Violin Point) Plots

Provides two methods of plotting categorical scatter plots such that the arrangement of points within a category reflects the density of data at that region, and avoids over-plotting.

Maintained by Erik Clarke. Last updated 5 months ago.

550 stars 15.45 score 7.6k scripts 84 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

hms-dbmi

UpSetR:A More Scalable Alternative to Venn and Euler Diagrams for Visualizing Intersecting Sets

Creates visualizations of intersecting sets using a novel matrix design, along with visualizations of several common set, element and attribute related tasks (Conway 2017) <doi:10.1093/bioinformatics/btx364>.

Maintained by Jake Conway. Last updated 4 years ago.

gehlenborglab ggplot2 upset upsetr visualization

781 stars 15.33 score 4.8k scripts 42 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

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 1 days ago.

1 stars 14.99 score 3.2k scripts 948 dependents

bioc

DOSE:Disease Ontology Semantic and Enrichment analysis

This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring semantic similarities among DO terms and gene products. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented for discovering disease associations of high-throughput biological data.

Maintained by Guangchuang Yu. Last updated 5 months ago.

annotation visualization multiplecomparison genesetenrichment pathways software disease-ontology enrichment-analysis semantic-similarity

119 stars 14.97 score 2.0k scripts 61 dependents

mjskay

ggdist:Visualizations of Distributions and Uncertainty

Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include but are not limited to: points with multiple uncertainty intervals, eye plots (Spiegelhalter D., 1999) <https://ideas.repec.org/a/bla/jorssa/v162y1999i1p45-58.html>, density plots, gradient plots, dot plots (Wilkinson L., 1999) <doi:10.1080/00031305.1999.10474474>, quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) <doi:10.1145/2858036.2858558>, complementary cumulative distribution function barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) <doi:10.1145/3173574.3173718>, and fit curves with multiple uncertainty ribbons.

Maintained by Matthew Kay. Last updated 4 months ago.

ggplot2 uncertainty uncertainty-visualization visualization cpp

859 stars 14.95 score 3.1k scripts 62 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

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

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

bioc

maftools:Summarize, Analyze and Visualize MAF Files

Analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. This package provides various functions to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualzations with minimal effort.

Maintained by Anand Mayakonda. Last updated 5 months ago.

datarepresentation dnaseq visualization drivermutation variantannotation featureextraction classification somaticmutation sequencing functionalgenomics survival bioinformatics cancer-genome-atlas cancer-genomics genomics maf-files tcga curl bzip2 xz-utils zlib

461 stars 14.58 score 948 scripts 18 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 21 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

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

r-spatial

mapview:Interactive Viewing of Spatial Data in R

Quickly and conveniently create interactive visualisations of spatial data with or without background maps. Attributes of displayed features are fully queryable via pop-up windows. Additional functionality includes methods to visualise true- and false-color raster images and bounding boxes.

Maintained by Tim Appelhans. Last updated 3 months ago.

gis leaflet maps spatial visualization web-mapping

526 stars 14.39 score 7.3k scripts 27 dependents

davidgohel

ggiraph:Make 'ggplot2' Graphics Interactive

Create interactive 'ggplot2' graphics using 'htmlwidgets'.

Maintained by David Gohel. Last updated 3 days ago.

libpng cpp

822 stars 14.37 score 4.1k scripts 35 dependents

raivokolde

pheatmap:Pretty Heatmaps

Implementation of heatmaps that offers more control over dimensions and appearance.

Maintained by Raivo Kolde. Last updated 6 years ago.

246 stars 14.36 score 22k scripts 231 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

eliocamp

ggnewscale:Multiple Fill and Colour Scales in 'ggplot2'

Use multiple fill and colour scales in 'ggplot2'.

Maintained by Elio Campitelli. Last updated 1 months ago.

ggplot2

414 stars 14.18 score 4.9k scripts 136 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

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

bioc

qvalue:Q-value estimation for false discovery rate control

This package takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values and local FDR values. The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. The local FDR measures the posterior probability the null hypothesis is true given the test's p-value. Various plots are automatically generated, allowing one to make sensible significance cut-offs. Several mathematical results have recently been shown on the conservative accuracy of the estimated q-values from this software. The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining.

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

multiplecomparisons

116 stars 14.07 score 3.0k scripts 139 dependents

teunbrand

ggh4x:Hacks for 'ggplot2'

A 'ggplot2' extension that does a variety of little helpful things. The package extends 'ggplot2' facets through customisation, by setting individual scales per panel, resizing panels and providing nested facets. Also allows multiple colour and fill scales per plot. Also hosts a smaller collection of stats, geoms and axis guides.

Maintained by Teun van den Brand. Last updated 12 days ago.

ggplot-extension ggplot2

617 stars 14.06 score 4.4k scripts 21 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

hrbrmstr

hrbrthemes:Additional Themes, Theme Components and Utilities for 'ggplot2'

A compilation of extra 'ggplot2' themes, scales and utilities, including a spell check function for plot label fields and an overall emphasis on typography. A copy of the 'Google' font 'Roboto Condensed' is also included.

Maintained by Bob Rudis. Last updated 17 days ago.

data-visualization datavisualization ggplot-extension ggplot2 ggplot2-scales ggplot2-themes visualization

1.3k stars 13.92 score 13k scripts 15 dependents

bioc

phyloseq:Handling and analysis of high-throughput microbiome census data

phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.

Maintained by Paul J. McMurdie. Last updated 5 months ago.

immunooncology sequencing microbiome metagenomics clustering classification multiplecomparison geneticvariability

600 stars 13.91 score 8.4k scripts 38 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 3 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

r-spatial

rgee:R Bindings for Calling the 'Earth Engine' API

Earth Engine <https://earthengine.google.com/> client library for R. All of the 'Earth Engine' API classes, modules, and functions are made available. Additional functions implemented include importing (exporting) of Earth Engine spatial objects, extraction of time series, interactive map display, assets management interface, and metadata display. See <https://r-spatial.github.io/rgee/> for further details.

Maintained by Cesar Aybar. Last updated 5 days ago.

earth-engine earthengine google-earth-engine googleearthengine spatial-analysis spatial-data

717 stars 13.77 score 1.9k scripts 3 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 4 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

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

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 1 days ago.

terra ggplot-extension r-spatial rspatial

190 stars 13.59 score 1.9k scripts 26 dependents

andrie

ggdendro:Create Dendrograms and Tree Diagrams Using 'ggplot2'

This is a set of tools for dendrograms and tree plots using 'ggplot2'. The 'ggplot2' philosophy is to clearly separate data from the presentation. Unfortunately the plot method for dendrograms plots directly to a plot device without exposing the data. The 'ggdendro' package resolves this by making available functions that extract the dendrogram plot data. The package provides implementations for 'tree', 'rpart', as well as diana and agnes (from 'cluster') diagrams.

Maintained by Andrie de Vries. Last updated 4 months ago.

ggplot2

86 stars 13.54 score 3.9k scripts 62 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

daattali

ggExtra:Add Marginal Histograms to 'ggplot2', and More 'ggplot2' Enhancements

Collection of functions and layers to enhance 'ggplot2'. The flagship function is 'ggMarginal()', which can be used to add marginal histograms/boxplots/density plots to 'ggplot2' scatterplots.

Maintained by Dean Attali. Last updated 10 months ago.

ggplot2 ggplot2-enhancements marginal-plots

387 stars 13.45 score 3.3k scripts 28 dependents

modeloriented

DALEX:moDel Agnostic Language for Exploration and eXplanation

Any unverified black box model is the path to failure. Opaqueness leads to distrust. Distrust leads to ignoration. Ignoration leads to rejection. DALEX package xrays any model and helps to explore and explain its behaviour. Machine Learning (ML) models are widely used and have various applications in classification or regression. Models created with boosting, bagging, stacking or similar techniques are often used due to their high performance. But such black-box models usually lack direct interpretability. DALEX package contains various methods that help to understand the link between input variables and model output. Implemented methods help to explore the model on the level of a single instance as well as a level of the whole dataset. All model explainers are model agnostic and can be compared across different models. DALEX package is the cornerstone for 'DrWhy.AI' universe of packages for visual model exploration. Find more details in (Biecek 2018) <https://jmlr.org/papers/v19/18-416.html>.

Maintained by Przemyslaw Biecek. Last updated 2 months ago.

black-box dalex data-science explainable-ai explainable-artificial-intelligence explainable-ml explanations explanatory-model-analysis fairness iml interpretability interpretable-machine-learning machine-learning model-visualization predictive-modeling responsible-ai responsible-ml xai

1.4k stars 13.40 score 876 scripts 21 dependents

vpetukhov

ggrastr:Rasterize Layers for 'ggplot2'

Rasterize only specific layers of a 'ggplot2' plot while simultaneously keeping all labels and text in vector format. This allows users to keep plots within the reasonable size limit without loosing vector properties of the scale-sensitive information.

Maintained by Evan Biederstedt. Last updated 2 years ago.

220 stars 13.37 score 1.9k scripts 53 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

trafficonese

leaflet.extras:Extra Functionality for 'leaflet' Package

The 'leaflet' JavaScript library provides many plugins some of which are available in the core 'leaflet' package, but there are many more. It is not possible to support them all in the core 'leaflet' package. This package serves as an add-on to the 'leaflet' package by providing extra functionality via 'leaflet' plugins.

Maintained by Sebastian Gatscha. Last updated 3 months ago.

data-visualization geospatial leaflet

218 stars 13.27 score 2.5k scripts 25 dependents

ropensci

rgbif:Interface to the Global Biodiversity Information Facility API

A programmatic interface to the Web Service methods provided by the Global Biodiversity Information Facility (GBIF; <https://www.gbif.org/developer/summary>). GBIF is a database of species occurrence records from sources all over the globe. rgbif includes functions for searching for taxonomic names, retrieving information on data providers, getting species occurrence records, getting counts of occurrence records, and using the GBIF tile map service to make rasters summarizing huge amounts of data.

Maintained by John Waller. Last updated 18 days ago.

gbif specimens api web-services occurrences species taxonomy biodiversity data lifewatch oscibio spocc

161 stars 13.26 score 2.1k scripts 20 dependents

guangchuangyu

ggplotify:Convert Plot to 'grob' or 'ggplot' Object

Convert plot function call (using expression or formula) to 'grob' or 'ggplot' object that compatible to the 'grid' and 'ggplot2' ecosystem. With this package, we are able to e.g. using 'cowplot' to align plots produced by 'base' graphics, 'ComplexHeatmap', 'eulerr', 'grid', 'lattice', 'magick', 'pheatmap', 'vcd' etc. by converting them to 'ggplot' objects.

Maintained by Guangchuang Yu. Last updated 1 years ago.

baseplot ggplot2 grid lattice upsetr vcd

108 stars 13.23 score 2.0k scripts 174 dependents

easystats

see:Model Visualisation Toolbox for 'easystats' and 'ggplot2'

Provides plotting utilities supporting packages in the 'easystats' ecosystem (<https://github.com/easystats/easystats>) and some extra themes, geoms, and scales for 'ggplot2'. Color scales are based on <https://materialui.co/>. References: Lüdecke et al. (2021) <doi:10.21105/joss.03393>.

Maintained by Indrajeet Patil. Last updated 20 days ago.

data-visualization easystats ggplot2 hacktoberfest plotting see statistics visualisation visualization

902 stars 13.22 score 2.0k scripts 3 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

bioc

dada2:Accurate, high-resolution sample inference from amplicon sequencing data

The dada2 package infers exact amplicon sequence variants (ASVs) from high-throughput amplicon sequencing data, replacing the coarser and less accurate OTU clustering approach. The dada2 pipeline takes as input demultiplexed fastq files, and outputs the sequence variants and their sample-wise abundances after removing substitution and chimera errors. Taxonomic classification is available via a native implementation of the RDP naive Bayesian classifier, and species-level assignment to 16S rRNA gene fragments by exact matching.

Maintained by Benjamin Callahan. Last updated 5 months ago.

immunooncology microbiome sequencing classification metagenomics amplicon bioconductor bioinformatics metabarcoding taxonomy cpp

487 stars 13.17 score 3.0k scripts 4 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

runehaubo

lmerTest:Tests in Linear Mixed Effects Models

Provides p-values in type I, II or III anova and summary tables for lmer model fits (cf. lme4) via Satterthwaite's degrees of freedom method. A Kenward-Roger method is also available via the pbkrtest package. Model selection methods include step, drop1 and anova-like tables for random effects (ranova). Methods for Least-Square means (LS-means) and tests of linear contrasts of fixed effects are also available.

Maintained by Rune Haubo Bojesen Christensen. Last updated 4 years ago.

52 stars 13.09 score 13k scripts 91 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

tagteam

riskRegression:Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks

Implementation of the following methods for event history analysis. Risk regression models for survival endpoints also in the presence of competing risks are fitted using binomial regression based on a time sequence of binary event status variables. A formula interface for the Fine-Gray regression model and an interface for the combination of cause-specific Cox regression models. A toolbox for assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance is measured by the Brier score and the area under the ROC curve for binary possibly time-dependent outcome. Inverse probability of censoring weighting and pseudo values are used to deal with right censored data. Lists of risk markers and lists of risk models are assessed simultaneously. Cross-validation repeatedly splits the data, trains the risk prediction models on one part of each split and then summarizes and compares the performance across splits.

Maintained by Thomas Alexander Gerds. Last updated 1 months ago.

openblas cpp

47 stars 13.07 score 736 scripts 37 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

giuseppec

iml:Interpretable Machine Learning

Interpretability methods to analyze the behavior and predictions of any machine learning model. Implemented methods are: Feature importance described by Fisher et al. (2018) <doi:10.48550/arxiv.1801.01489>, accumulated local effects plots described by Apley (2018) <doi:10.48550/arxiv.1612.08468>, partial dependence plots described by Friedman (2001) <www.jstor.org/stable/2699986>, individual conditional expectation ('ice') plots described by Goldstein et al. (2013) <doi:10.1080/10618600.2014.907095>, local models (variant of 'lime') described by Ribeiro et. al (2016) <doi:10.48550/arXiv.1602.04938>, the Shapley Value described by Strumbelj et. al (2014) <doi:10.1007/s10115-013-0679-x>, feature interactions described by Friedman et. al <doi:10.1214/07-AOAS148> and tree surrogate models.

Maintained by Giuseppe Casalicchio. Last updated 1 months ago.

495 stars 13.05 score 642 scripts 4 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

easystats

easystats:Framework for Easy Statistical Modeling, Visualization, and Reporting

A meta-package that installs and loads a set of packages from 'easystats' ecosystem in a single step. This collection of packages provide a unifying and consistent framework for statistical modeling, visualization, and reporting. Additionally, it provides articles targeted at instructors for teaching 'easystats', and a dashboard targeted at new R users for easily conducting statistical analysis by accessing summary results, model fit indices, and visualizations with minimal programming.

Maintained by Daniel Lüdecke. Last updated 27 days ago.

dataanalytics datascience easystats hacktoberfest models performance-metrics regression-models statistics

1.1k stars 13.01 score 1.8k scripts 1 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

ngreifer

cobalt:Covariate Balance Tables and Plots

Generate balance tables and plots for covariates of groups preprocessed through matching, weighting or subclassification, for example, using propensity scores. Includes integration with 'MatchIt', 'WeightIt', 'MatchThem', 'twang', 'Matching', 'optmatch', 'CBPS', 'ebal', 'cem', 'sbw', and 'designmatch' for assessing balance on the output of their preprocessing functions. Users can also specify data for balance assessment not generated through the above packages. Also included are methods for assessing balance in clustered or multiply imputed data sets or data sets with multi-category, continuous, or longitudinal treatments.

Maintained by Noah Greifer. Last updated 12 months ago.

causal-inference propensity-scores

75 stars 12.98 score 1.0k scripts 8 dependents

michaelhallquist

MplusAutomation:An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus

Leverages the R language to automate latent variable model estimation and interpretation using 'Mplus', a powerful latent variable modeling program developed by Muthen and Muthen (<https://www.statmodel.com>). Specifically, this package provides routines for creating related groups of models, running batches of models, and extracting and tabulating model parameters and fit statistics.

Maintained by Michael Hallquist. Last updated 6 days ago.

86 stars 12.92 score 664 scripts 13 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 17 days ago.

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

65 stars 12.89 score 900 scripts 11 dependents

bioc

iSEE:Interactive SummarizedExperiment Explorer

Create an interactive Shiny-based graphical user interface for exploring data stored in SummarizedExperiment objects, including row- and column-level metadata. The interface supports transmission of selections between plots and tables, code tracking, interactive tours, interactive or programmatic initialization, preservation of app state, and extensibility to new panel types via S4 classes. Special attention is given to single-cell data in a SingleCellExperiment object with visualization of dimensionality reduction results.

Maintained by Kevin Rue-Albrecht. Last updated 25 days ago.

cellbasedassays clustering dimensionreduction featureextraction geneexpression gui immunooncology shinyapps singlecell transcription transcriptomics visualization dimension-reduction feature-extraction gene-expression hacktoberfest human-cell-atlas shiny single-cell

225 stars 12.86 score 380 scripts 9 dependents

kassambara

ggcorrplot:Visualization of a Correlation Matrix using 'ggplot2'

The 'ggcorrplot' package can be used to visualize easily a correlation matrix using 'ggplot2'. It provides a solution for reordering the correlation matrix and displays the significance level on the plot. It also includes a function for computing a matrix of correlation p-values.

Maintained by Alboukadel Kassambara. Last updated 2 years ago.

190 stars 12.86 score 6.9k scripts 22 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

alexkowa

EnvStats:Package for Environmental Statistics, Including US EPA Guidance

Graphical and statistical analyses of environmental data, with focus on analyzing chemical concentrations and physical parameters, usually in the context of mandated environmental monitoring. Major environmental statistical methods found in the literature and regulatory guidance documents, with extensive help that explains what these methods do, how to use them, and where to find them in the literature. Numerous built-in data sets from regulatory guidance documents and environmental statistics literature. Includes scripts reproducing analyses presented in the book "EnvStats: An R Package for Environmental Statistics" (Millard, 2013, Springer, ISBN 978-1-4614-8455-4, <doi:10.1007/978-1-4614-8456-1>).

Maintained by Alexander Kowarik. Last updated 12 hours ago.

26 stars 12.85 score 2.4k scripts 47 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

chr1swallace

coloc:Colocalisation Tests of Two Genetic Traits

Performs the colocalisation tests described in Giambartolomei et al (2013) <doi:10.1371/journal.pgen.1004383>, Wallace (2020) <doi:10.1371/journal.pgen.1008720>, Wallace (2021) <doi:10.1371/journal.pgen.1009440>, Pullin and Wallace (2025) <doi:10.1101/2024.08.21.608957>.

Maintained by Chris Wallace. Last updated 4 days ago.

164 stars 12.68 score 916 scripts 3 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

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

wilkox

treemapify:Draw Treemaps in 'ggplot2'

Provides 'ggplot2' geoms for drawing treemaps.

Maintained by David Wilkins. Last updated 10 months ago.

data-visualisation ggplot2 treemap

215 stars 12.58 score 1.6k scripts 9 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

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

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

rstudio

flexdashboard:R Markdown Format for Flexible Dashboards

Format for converting an R Markdown document to a grid oriented dashboard. The dashboard flexibly adapts the size of it's components to the containing web page.

Maintained by Garrick Aden-Buie. Last updated 11 months ago.

823 stars 12.49 score 4.5k scripts 8 dependents

r-spatialecology

landscapemetrics:Landscape Metrics for Categorical Map Patterns

Calculates landscape metrics for categorical landscape patterns in a tidy workflow. 'landscapemetrics' reimplements the most common metrics from 'FRAGSTATS' (<https://www.fragstats.org/>) and new ones from the current literature on landscape metrics. This package supports 'terra' SpatRaster objects as input arguments. It further provides utility functions to visualize patches, select metrics and building blocks to develop new metrics.

Maintained by Maximilian H.K. Hesselbarth. Last updated 2 months ago.

landscape-ecology landscape-metrics raster spatial cpp

240 stars 12.47 score 584 scripts 4 dependents

r-spatial

leafem:'leaflet' Extensions for 'mapview'

Provides extensions for packages 'leaflet' & 'mapdeck', many of which are used by package 'mapview'. Focus is on functionality readily available in Geographic Information Systems such as 'Quantum GIS'. Includes functions to display coordinates of mouse pointer position, query image values via mouse pointer and zoom-to-layer buttons. Additionally, provides a feature type agnostic function to add points, lines, polygons to a map.

Maintained by Tim Appelhans. Last updated 1 months ago.

108 stars 12.41 score 704 scripts 55 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

bioc

scDblFinder:scDblFinder

The scDblFinder package gathers various methods for the detection and handling of doublets/multiplets in single-cell sequencing data (i.e. multiple cells captured within the same droplet or reaction volume). It includes methods formerly found in the scran package, the new fast and comprehensive scDblFinder method, and a reimplementation of the Amulet detection method for single-cell ATAC-seq.

Maintained by Pierre-Luc Germain. Last updated 11 days ago.

preprocessing singlecell rnaseq atacseq doublets single-cell

184 stars 12.38 score 888 scripts 1 dependents

trevorld

ggpattern:'ggplot2' Pattern Geoms

Provides 'ggplot2' geoms filled with various patterns. Includes a patterned version of every 'ggplot2' geom that has a region that can be filled with a pattern. Provides a suite of 'ggplot2' aesthetics and scales for controlling pattern appearances. Supports over a dozen builtin patterns (every pattern implemented by 'gridpattern') as well as allowing custom user-defined patterns.

Maintained by Trevor L. Davis. Last updated 2 months ago.

370 stars 12.36 score 1.7k scripts 3 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

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

eliocamp

metR:Tools for Easier Analysis of Meteorological Fields

Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.

Maintained by Elio Campitelli. Last updated 12 days ago.

atmospheric-science ggplot2 visualization

146 stars 12.30 score 1000 scripts 22 dependents

bioc

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

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

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

dnamethylation cpp

37 stars 12.26 score 676 scripts 15 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

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

quentingronau

bridgesampling:Bridge Sampling for Marginal Likelihoods and Bayes Factors

Provides functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and normalizing constants in general, via different versions of bridge sampling (Meng & Wong, 1996, <https://www3.stat.sinica.edu.tw/statistica/j6n4/j6n43/j6n43.htm>). Gronau, Singmann, & Wagenmakers (2020) <doi:10.18637/jss.v092.i10>.

Maintained by Quentin F. Gronau. Last updated 2 years ago.

32 stars 12.19 score 314 scripts 55 dependents

steffenmoritz

imputeTS:Time Series Missing Value Imputation

Imputation (replacement) of missing values in univariate time series. Offers several imputation functions and missing data plots. Available imputation algorithms include: 'Mean', 'LOCF', 'Interpolation', 'Moving Average', 'Seasonal Decomposition', 'Kalman Smoothing on Structural Time Series models', 'Kalman Smoothing on ARIMA models'. Published in Moritz and Bartz-Beielstein (2017) <doi:10.32614/RJ-2017-009>.

Maintained by Steffen Moritz. Last updated 3 years ago.

data-visualization imputation imputation-algorithm imputets missing-data time-series cpp

162 stars 12.18 score 1.9k scripts 27 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

tagteam

prodlim:Product-Limit Estimation for Censored Event History Analysis

Fast and user friendly implementation of nonparametric estimators for censored event history (survival) analysis. Kaplan-Meier and Aalen-Johansen method.

Maintained by Thomas A. Gerds. Last updated 27 days ago.

7 stars 12.18 score 1000 scripts 462 dependents

bioc

EnhancedVolcano:Publication-ready volcano plots with enhanced colouring and labeling

Volcano plots represent a useful way to visualise the results of differential expression analyses. Here, we present a highly-configurable function that produces publication-ready volcano plots. EnhancedVolcano will attempt to fit as many point labels in the plot window as possible, thus avoiding 'clogging' up the plot with labels that could not otherwise have been read. Other functionality allows the user to identify up to 4 different types of attributes in the same plot space via colour, shape, size, and shade parameter configurations.

Maintained by Kevin Blighe. Last updated 5 months ago.

rnaseq geneexpression transcription differentialexpression immunooncology

427 stars 12.16 score 2.7k scripts 1 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

reconhub

incidence:Compute, Handle, Plot and Model Incidence of Dated Events

Provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class 'incidence' is used to store computed incidence and can be easily manipulated, subsetted, and plotted. In addition, log-linear models can be fitted to 'incidence' objects using 'fit'. This package is part of the RECON (<https://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.

Maintained by Tim Taylor. Last updated 8 months ago.

outbreak

58 stars 12.06 score 504 scripts 11 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

geomorphr

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

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

Maintained by Dean Adams. Last updated 2 months ago.

76 stars 12.05 score 700 scripts 6 dependents

allancameron

geomtextpath:Curved Text in 'ggplot2'

A 'ggplot2' extension that allows text to follow curved paths. Curved text makes it easier to directly label paths or neatly annotate in polar co-ordinates.

Maintained by Allan Cameron. Last updated 3 months ago.

631 stars 12.04 score 960 scripts 5 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

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

stefanedwards

lemon:Freshing Up your 'ggplot2' Plots

Functions for working with legends and axis lines of 'ggplot2', facets that repeat axis lines on all panels, and some 'knitr' extensions.

Maintained by Stefan McKinnon Edwards. Last updated 5 months ago.

axis-lines facets ggplot-extension ggplot2 knitr legend ticks visualization

190 stars 11.98 score 1.7k scripts 4 dependents

baptiste

egg:Extensions for 'ggplot2': Custom Geom, Custom Themes, Plot Alignment, Labelled Panels, Symmetric Scales, and Fixed Panel Size

Miscellaneous functions to help customise 'ggplot2' objects. High-level functions are provided to post-process 'ggplot2' layouts and allow alignment between plot panels, as well as setting panel sizes to fixed values. Other functions include a custom 'geom', and helper functions to enforce symmetric scales or add tags to facetted plots.

Maintained by Baptiste Auguie. Last updated 4 years ago.

13 stars 11.95 score 2.4k scripts 69 dependents

exaexa

scattermore:Scatterplots with More Points

C-based conversion of large scatterplot data to rasters plus other operations such as data blurring or data alpha blending. Speeds up plotting of data with millions of points.

Maintained by Mirek Kratochvil. Last updated 1 years ago.

performance plot scatterplot visualization cpp

244 stars 11.95 score 596 scripts 85 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

jamesramsay5

fda:Functional Data Analysis

These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer and in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. Matlab versions are available by ftp from <https://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.

Maintained by James Ramsay. Last updated 4 months ago.

3 stars 11.88 score 2.0k scripts 142 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

epiforecasts

EpiNow2:Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters

Estimates the time-varying reproduction number, rate of spread, and doubling time using a range of open-source tools (Abbott et al. (2020) <doi:10.12688/wellcomeopenres.16006.1>), and current best practices (Gostic et al. (2020) <doi:10.1101/2020.06.18.20134858>). It aims to help users avoid some of the limitations of naive implementations in a framework that is informed by community feedback and is actively supported.

Maintained by Sebastian Funk. Last updated 1 months ago.

backcalculation covid-19 gaussian-processes open-source reproduction-number stan cpp

123 stars 11.86 score 210 scripts

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

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

bioc

methylKit:DNA methylation analysis from high-throughput bisulfite sequencing results

methylKit is an R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from RRBS and its variants, but also target-capture methods and whole genome bisulfite sequencing. It also has functions to analyze base-pair resolution 5hmC data from experimental protocols such as oxBS-Seq and TAB-Seq. Methylation calling can be performed directly from Bismark aligned BAM files.

Maintained by Altuna Akalin. Last updated 1 months ago.

dnamethylation sequencing methylseq genome-biology methylation statistical-analysis visualization curl bzip2 xz-utils zlib cpp

224 stars 11.78 score 578 scripts 3 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

daattali

colourpicker:A Colour Picker Tool for Shiny and for Selecting Colours in Plots

A colour picker that can be used as an input in 'Shiny' apps or Rmarkdown documents. The colour picker supports alpha opacity, custom colour palettes, and many more options. A Plot Colour Helper tool is available as an 'RStudio' Addin, which helps you pick colours to use in your plots. A more generic Colour Picker 'RStudio' Addin is also provided to let you select colours to use in your R code.

Maintained by Dean Attali. Last updated 8 months ago.

rstudio-addin shiny shiny-r

222 stars 11.76 score 936 scripts 120 dependents

briatte

ggnetwork:Geometries to Plot Networks with 'ggplot2'

Geometries to plot network objects with 'ggplot2'.

Maintained by François Briatte. Last updated 9 months ago.

ggplot2 network-visualization

149 stars 11.74 score 766 scripts 15 dependents

google

CausalImpact:Inferring Causal Effects using Bayesian Structural Time-Series Models

Implements a Bayesian approach to causal impact estimation in time series, as described in Brodersen et al. (2015) <DOI:10.1214/14-AOAS788>. See the package documentation on GitHub <https://google.github.io/CausalImpact/> to get started.

Maintained by Alain Hauser. Last updated 2 years ago.

1.7k stars 11.73 score 276 scripts 2 dependents

bgreenwell

pdp:Partial Dependence Plots

A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.

Maintained by Brandon M. Greenwell. Last updated 3 years ago.

black-box-model machine-learning partial-dependence-function partial-dependence-plot visualization

93 stars 11.72 score 1.1k scripts 8 dependents

jbryer

likert:Analysis and Visualization Likert Items

An approach to analyzing Likert response items, with an emphasis on visualizations. The stacked bar plot is the preferred method for presenting Likert results. Tabular results are also implemented along with density plots to assist researchers in determining whether Likert responses can be used quantitatively instead of qualitatively. See the likert(), summary.likert(), and plot.likert() functions to get started.

Maintained by Jason Bryer. Last updated 6 days ago.

data-science visualization

310 stars 11.71 score 480 scripts 2 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

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

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 13 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

ngreifer

WeightIt:Weighting for Covariate Balance in Observational Studies

Generates balancing weights for causal effect estimation in observational studies with binary, multi-category, or continuous point or longitudinal treatments by easing and extending the functionality of several R packages and providing in-house estimation methods. Available methods include those that rely on parametric modeling, optimization, and machine learning. Also allows for assessment of weights and checking of covariate balance by interfacing directly with the 'cobalt' package. Methods for estimating weighted regression models that take into account uncertainty in the estimation of the weights via M-estimation or bootstrapping are available. See the vignette "Installing Supporting Packages" for instructions on how to install any package 'WeightIt' uses, including those that may not be on CRAN.

Maintained by Noah Greifer. Last updated 20 days ago.

causal-inference inverse-probability-weights observational-study propensity-scores

112 stars 11.58 score 508 scripts 3 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

robjhyndman

tsfeatures:Time Series Feature Extraction

Methods for extracting various features from time series data. The features provided are those from Hyndman, Wang and Laptev (2013) <doi:10.1109/ICDMW.2015.104>, Kang, Hyndman and Smith-Miles (2017) <doi:10.1016/j.ijforecast.2016.09.004> and from Fulcher, Little and Jones (2013) <doi:10.1098/rsif.2013.0048>. Features include spectral entropy, autocorrelations, measures of the strength of seasonality and trend, and so on. Users can also define their own feature functions.

Maintained by Rob Hyndman. Last updated 8 months ago.

feature-extraction time-series

257 stars 11.55 score 268 scripts 22 dependents

tylermorganwall

rayshader:Create Maps and Visualize Data in 2D and 3D

Uses a combination of raytracing and multiple hill shading methods to produce 2D and 3D data visualizations and maps. Includes water detection and layering functions, programmable color palette generation, several built-in textures for hill shading, 2D and 3D plotting options, a built-in path tracer, 'Wavefront' OBJ file export, and the ability to save 3D visualizations to a 3D printable format.

Maintained by Tyler Morgan-Wall. Last updated 2 months ago.

cpp

2.1k stars 11.55 score 1.5k scripts 5 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

functionaldata

fdapace:Functional Data Analysis and Empirical Dynamics

A versatile package that provides implementation of various methods of Functional Data Analysis (FDA) and Empirical Dynamics. The core of this package is Functional Principal Component Analysis (FPCA), a key technique for functional data analysis, for sparsely or densely sampled random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm. This core algorithm yields covariance and mean functions, eigenfunctions and principal component (scores), for both functional data and derivatives, for both dense (functional) and sparse (longitudinal) sampling designs. For sparse designs, it provides fitted continuous trajectories with confidence bands, even for subjects with very few longitudinal observations. PACE is a viable and flexible alternative to random effects modeling of longitudinal data. There is also a Matlab version (PACE) that contains some methods not available on fdapace and vice versa. Updates to fdapace were supported by grants from NIH Echo and NSF DMS-1712864 and DMS-2014626. Please cite our package if you use it (You may run the command citation("fdapace") to get the citation format and bibtex entry). References: Wang, J.L., Chiou, J., Müller, H.G. (2016) <doi:10.1146/annurev-statistics-041715-033624>; Chen, K., Zhang, X., Petersen, A., Müller, H.G. (2017) <doi:10.1007/s12561-015-9137-5>.

Maintained by Yidong Zhou. Last updated 9 months ago.

cpp

31 stars 11.54 score 474 scripts 25 dependents

bioc

systemPipeR:systemPipeR: Workflow Environment for Data Analysis and Report Generation

systemPipeR is a multipurpose data analysis workflow environment that unifies R with command-line tools. It enables scientists to analyze many types of large- or small-scale data on local or distributed computer systems with a high level of reproducibility, scalability and portability. At its core is a command-line interface (CLI) that adopts the Common Workflow Language (CWL). This design allows users to choose for each analysis step the optimal R or command-line software. It supports both end-to-end and partial execution of workflows with built-in restart functionalities. Efficient management of complex analysis tasks is accomplished by a flexible workflow control container class. Handling of large numbers of input samples and experimental designs is facilitated by consistent sample annotation mechanisms. As a multi-purpose workflow toolkit, systemPipeR enables users to run existing workflows, customize them or design entirely new ones while taking advantage of widely adopted data structures within the Bioconductor ecosystem. Another important core functionality is the generation of reproducible scientific analysis and technical reports. For result interpretation, systemPipeR offers a wide range of plotting functionality, while an associated Shiny App offers many useful functionalities for interactive result exploration. The vignettes linked from this page include (1) a general introduction, (2) a description of technical details, and (3) a collection of workflow templates.

Maintained by Thomas Girke. Last updated 5 months ago.

genetics infrastructure dataimport sequencing rnaseq riboseq chipseq methylseq snp geneexpression coverage genesetenrichment alignment qualitycontrol immunooncology reportwriting workflowstep workflowmanagement

53 stars 11.52 score 344 scripts 3 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

omarwagih

ggseqlogo:A 'ggplot2' Extension for Drawing Publication-Ready Sequence Logos

The extensive range of functions provided by this package makes it possible to draw highly versatile sequence logos. Features include, but not limited to, modifying colour schemes and fonts used to draw the logo, generating multiple logo plots, and aiding the visualisation with annotations. Sequence logos can easily be combined with other plots 'ggplot2' plots.

Maintained by Omar Wagih. Last updated 6 months ago.

211 stars 11.48 score 786 scripts 13 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

privefl

bigsnpr:Analysis of Massive SNP Arrays

Easy-to-use, efficient, flexible and scalable tools for analyzing massive SNP arrays. Privé et al. (2018) <doi:10.1093/bioinformatics/bty185>.

Maintained by Florian Privé. Last updated 25 days ago.

big-data bioinformatics memory-mapped-file parallel-computing polygenic-scores population-structure-inference snp-data statistical-methods openblas zlib cpp openmp

200 stars 11.44 score 1.5k scripts 3 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

sachaepskamp

qgraph:Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation

Fork of qgraph - Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.

Maintained by Sacha Epskamp. Last updated 1 years ago.

cpp

69 stars 11.43 score 1.2k scripts 63 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