Showing 200 of total 3333 results (show query)

adeckmyn

maps:Draw Geographical Maps

Display of maps. Projection code and larger maps are in separate packages ('mapproj' and 'mapdata').

Maintained by Alex Deckmyn. Last updated 2 months ago.

152.7 match 24 stars 14.70 score 19k scripts 490 dependents

andysouth

rworldmap:Mapping Global Data

Enables mapping of country level and gridded user datasets.

Maintained by Andy South. Last updated 2 years ago.

64.3 match 30 stars 11.83 score 3.2k scripts 14 dependents

tidyverse

purrr:Functional Programming Tools

A complete and consistent functional programming toolkit for R.

Maintained by Hadley Wickham. Last updated 1 months ago.

functional-programming

10.4 match 1.3k stars 22.12 score 59k scripts 6.9k dependents

datastorm-open

visNetwork:Network Visualization using 'vis.js' Library

Provides an R interface to the 'vis.js' JavaScript charting library. It allows an interactive visualization of networks.

Maintained by Benoit Thieurmel. Last updated 2 years ago.

15.0 match 549 stars 15.14 score 4.1k scripts 195 dependents

bupaverse

processmapR:Construct Process Maps Using Event Data

Visualize event logs using directed graphs, i.e. process maps. Part of the 'bupaR' framework.

Maintained by Gert Janssenswillen. Last updated 7 months ago.

cpp

26.4 match 9 stars 7.70 score 169 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.

immunooncologymicroarraysequencingmetabolomicsmetagenomicsproteomicsgenepredictionmultiplecomparisonclassificationregressionbioconductorgenomicsgenomics-datagenomics-visualizationmultivariate-analysismultivariate-statisticsomicsr-pkgr-project

12.2 match 182 stars 13.71 score 1.3k scripts 22 dependents

clementcalenge

adehabitatMA:Tools to Deal with Raster Maps

A collection of tools to deal with raster maps.

Maintained by Clement Calenge. Last updated 6 months ago.

25.0 match 1 stars 6.34 score 43 scripts 15 dependents

bioc

annotate:Annotation for microarrays

Using R enviroments for annotation.

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

annotationpathwaysgo

12.4 match 11.41 score 812 scripts 243 dependents

nflverse

nflreadr:Download 'nflverse' Data

A minimal package for downloading data from 'GitHub' repositories of the 'nflverse' project.

Maintained by Tan Ho. Last updated 4 months ago.

nflnflfastrnflversesports-data

11.1 match 66 stars 12.46 score 476 scripts 10 dependents

arilamstein

choroplethrMaps:Contains Maps Used by the 'choroplethr' Package

Contains 3 maps. 1) US States 2) US Counties 3) Countries of the world.

Maintained by Ari Lamstein. Last updated 7 years ago.

28.5 match 4.80 score 418 scripts 1 dependents

open-eo

openeo:Client Interface for 'openEO' Servers

Access data and processing functionalities of 'openEO' compliant back-ends in R.

Maintained by Florian Lahn. Last updated 2 months ago.

openeoopeneo-user

15.0 match 64 stars 8.65 score 128 scripts

thinkr-open

togglr:'Toggl.com' Api for 'Rstudio'

Use the <https://toggl.com> time tracker api through R.

Maintained by Vincent Guyader. Last updated 1 years ago.

hacktoberfesttoggl-apitoggler

18.5 match 49 stars 6.81 score 33 scripts

fragla

eq5d:Methods for Analysing 'EQ-5D' Data and Calculating 'EQ-5D' Index Scores

EQ-5D is a popular health related quality of life instrument used in the clinical and economic evaluation of health care. Developed by the EuroQol group <https://euroqol.org/>, the instrument consists of two components: health state description and evaluation. For the description component a subject self-rates their health in terms of five dimensions; mobility, self-care, usual activities, pain/discomfort, and anxiety/depression using either a three-level (EQ-5D-3L, <https://euroqol.org/information-and-support/euroqol-instruments/eq-5d-3l/>) or a five-level (EQ-5D-5L, <https://euroqol.org/information-and-support/euroqol-instruments/eq-5d-5l/>) scale. Frequently the scores on these five dimensions are converted to a single utility index using country specific value sets, which can be used in the clinical and economic evaluation of health care as well as in population health surveys. The eq5d package provides methods to calculate index scores from a subject's dimension scores. 32 TTO and 11 VAS EQ-5D-3L value sets including those for countries in Szende et al (2007) <doi:10.1007/1-4020-5511-0> and Szende et al (2014) <doi:10.1007/978-94-007-7596-1>, 47 EQ-5D-5L EQ-VT value sets, the EQ-5D-5L crosswalk value sets developed by van Hout et al. (2012) <doi:10.1016/j.jval.2012.02.008>, the crosswalk value sets for Bermuda, Jordan and Russia and the reverse crosswalk value sets. 10 EQ-5D-Y value sets are also included as are the NICE 'DSU' age-sex based EQ-5D-3L to EQ-5D-5L and EQ-5D-5L to EQ-5D-3L mappings. Methods are also included for the analysis of EQ-5D profiles, including those from the book "Methods for Analyzing and Reporting EQ-5D data" by Devlin et al. (2020) <doi:10.1007/978-3-030-47622-9>. Additionally a shiny web tool is included to enable the calculation, visualisation and automated statistical analysis of EQ-5D data via a web browser using EQ-5D dimension scores stored in CSV or Excel files.

Maintained by Fraser Morton. Last updated 15 days ago.

14.3 match 22 stars 8.19 score 37 scripts

mthrun

DataVisualizations:Visualizations of High-Dimensional Data

Gives access to data visualisation methods that are relevant from the data scientist's point of view. The flagship idea of 'DataVisualizations' is the mirrored density plot (MD-plot) for either classified or non-classified multivariate data published in Thrun, M.C. et al.: "Analyzing the Fine Structure of Distributions" (2020), PLoS ONE, <DOI:10.1371/journal.pone.0238835>. The MD-plot outperforms the box-and-whisker diagram (box plot), violin plot and bean plot and geom_violin plot of ggplot2. Furthermore, a collection of various visualization methods for univariate data is provided. In the case of exploratory data analysis, 'DataVisualizations' makes it possible to inspect the distribution of each feature of a dataset visually through a combination of four methods. One of these methods is the Pareto density estimation (PDE) of the probability density function (pdf). Additionally, visualizations of the distribution of distances using PDE, the scatter-density plot using PDE for two variables as well as the Shepard density plot and the Bland-Altman plot are presented here. Pertaining to classified high-dimensional data, a number of visualizations are described, such as f.ex. the heat map and silhouette plot. A political map of the world or Germany can be visualized with the additional information defined by a classification of countries or regions. By extending the political map further, an uncomplicated function for a Choropleth map can be used which is useful for measurements across a geographic area. For categorical features, the Pie charts, slope charts and fan plots, improved by the ABC analysis, become usable. More detailed explanations are found in the book by Thrun, M.C.: "Projection-Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>.

Maintained by Michael Thrun. Last updated 2 months ago.

cpp

14.5 match 7 stars 7.72 score 118 scripts 7 dependents

lbbe-software

MareyMap:Estimation of Meiotic Recombination Rates Using Marey Maps

Local recombination rates are graphically estimated across a genome using Marey maps.

Maintained by Aurรฉlie Siberchicot. Last updated 13 days ago.

21.0 match 1 stars 5.30 score 20 scripts

e-sensing

sits:Satellite Image Time Series Analysis for Earth Observation Data Cubes

An end-to-end toolkit for land use and land cover classification using big Earth observation data, based on machine learning methods applied to satellite image data cubes, as described in Simoes et al (2021) <doi:10.3390/rs13132428>. Builds regular data cubes from collections in AWS, Microsoft Planetary Computer, Brazil Data Cube, Copernicus Data Space Environment (CDSE), Digital Earth Africa, Digital Earth Australia, NASA HLS using the Spatio-temporal Asset Catalog (STAC) protocol (<https://stacspec.org/>) and the 'gdalcubes' R package developed by Appel and Pebesma (2019) <doi:10.3390/data4030092>. Supports visualization methods for images and time series and smoothing filters for dealing with noisy time series. Includes functions for quality assessment of training samples using self-organized maps as presented by Santos et al (2021) <doi:10.1016/j.isprsjprs.2021.04.014>. Includes methods to reduce training samples imbalance proposed by Chawla et al (2002) <doi:10.1613/jair.953>. Provides machine learning methods including support vector machines, random forests, extreme gradient boosting, multi-layer perceptrons, temporal convolutional neural networks proposed by Pelletier et al (2019) <doi:10.3390/rs11050523>, and temporal attention encoders by Garnot and Landrieu (2020) <doi:10.48550/arXiv.2007.00586>. Supports GPU processing of deep learning models using torch <https://torch.mlverse.org/>. Performs efficient classification of big Earth observation data cubes and includes functions for post-classification smoothing based on Bayesian inference as described by Camara et al (2024) <doi:10.3390/rs16234572>, and methods for active learning and uncertainty assessment. Supports region-based time series analysis using package supercells <https://jakubnowosad.com/supercells/>. Enables best practices for estimating area and assessing accuracy of land change as recommended by Olofsson et al (2014) <doi:10.1016/j.rse.2014.02.015>. Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core.

Maintained by Gilberto Camara. Last updated 1 months ago.

big-earth-datacbersearth-observationeo-datacubesgeospatialimage-time-seriesland-cover-classificationlandsatplanetary-computerr-spatialremote-sensingrspatialsatellite-image-time-seriessatellite-imagerysentinel-2stac-apistac-catalogcpp

11.5 match 494 stars 9.50 score 384 scripts

thinkr-open

fcuk:The Ultimate Helper for Clumsy Fingers

Automatically suggests a correction when a typo occurs.

Maintained by Vincent Guyader. Last updated 1 years ago.

errorfcuk

15.0 match 92 stars 7.05 score 49 scripts

ropensci

rnaturalearth:World Map Data from Natural Earth

Facilitates mapping by making natural earth map data from <https://www.naturalearthdata.com/> more easily available to R users.

Maintained by Philippe Massicotte. Last updated 1 days ago.

peer-reviewed

6.6 match 234 stars 15.52 score 7.2k scripts 47 dependents

thinkr-open

checkhelper:Deal with Check Outputs

Deal with packages 'check' outputs and reduce the risk of rejection by 'CRAN' by following policies.

Maintained by Sebastien Rochette. Last updated 1 years ago.

15.0 match 34 stars 6.74 score 18 scripts