Showing 31 of total 31 results (show query)
rstudio
renv:Project Environments
A dependency management toolkit for R. Using 'renv', you can create and manage project-local R libraries, save the state of these libraries to a 'lockfile', and later restore your library as required. Together, these tools can help make your projects more isolated, portable, and reproducible.
Maintained by Kevin Ushey. Last updated 3 days ago.
1.0k stars 18.59 score 1.5k scripts 114 dependents
ropensci
git2r:Provides Access to Git Repositories
Interface to the 'libgit2' library, which is a pure C implementation of the 'Git' core methods. Provides access to 'Git' repositories to extract data and running some basic 'Git' commands.
Maintained by Stefan Widgren. Last updated 22 hours ago.
gitgit-clientlibgit2libgit2-library
218 stars 13.93 score 836 scripts 46 dependentsrstudio
packrat:A Dependency Management System for Projects and their R Package Dependencies
Manage the R packages your project depends on in an isolated, portable, and reproducible way.
Maintained by Aron Atkins. Last updated 2 months ago.
406 stars 12.15 score 256 scripts 9 dependents
bioc
GenomicDataCommons:NIH / NCI Genomic Data Commons Access
Programmatically access the NIH / NCI Genomic Data Commons RESTful service.
Maintained by Sean Davis. Last updated 2 months ago.
dataimportsequencingapi-clientbioconductorbioinformaticscancercore-servicesdata-sciencegenomicsncitcgavignette
87 stars 11.94 score 238 scripts 12 dependents
shikokuchuo
mirai:Minimalist Async Evaluation Framework for R
Designed for simplicity, a 'mirai' evaluates an R expression asynchronously in a parallel process, locally or distributed over the network. The result is automatically available upon completion. Modern networking and concurrency, built on 'nanonext' and 'NNG' (Nanomsg Next Gen), ensures reliable and efficient scheduling over fast inter-process communications or TCP/IP secured by TLS. Distributed computing can launch remote resources via SSH or cluster managers. An inherently queued architecture handles many more tasks than available processes, and requires no storage on the file system. Innovative features include support for otherwise non-exportable reference objects, event-driven promises, and asynchronous parallel map.
Maintained by Charlie Gao. Last updated 8 days ago.
asyncasynchronous-tasksconcurrencydistributed-computinghigh-performance-computingparallel-computing
219 stars 11.89 score 130 scripts 7 dependentsbioc
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.
geneticsinfrastructuredataimportsequencingrnaseqriboseqchipseqmethylseqsnpgeneexpressioncoveragegenesetenrichmentalignmentqualitycontrolimmunooncologyreportwritingworkflowstepworkflowmanagement
53 stars 11.52 score 344 scripts 3 dependentsbioc
ChemmineR:Cheminformatics Toolkit for R
ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.
Maintained by Thomas Girke. Last updated 5 months ago.
cheminformaticsbiomedicalinformaticspharmacogeneticspharmacogenomicsmicrotitreplateassaycellbasedassaysvisualizationinfrastructuredataimportclusteringproteomicsmetabolomicscpp
15 stars 10.45 score 253 scripts 12 dependentsropensci
git2rdata:Store and Retrieve Data.frames in a Git Repository
The git2rdata package is an R package for writing and reading dataframes as plain text files. A metadata file stores important information. 1) Storing metadata allows to maintain the classes of variables. By default, git2rdata optimizes the data for file storage. The optimization is most effective on data containing factors. The optimization makes the data less human readable. The user can turn this off when they prefer a human readable format over smaller files. Details on the implementation are available in vignette("plain_text", package = "git2rdata"). 2) Storing metadata also allows smaller row based diffs between two consecutive commits. This is a useful feature when storing data as plain text files under version control. Details on this part of the implementation are available in vignette("version_control", package = "git2rdata"). Although we envisioned git2rdata with a git workflow in mind, you can use it in combination with other version control systems like subversion or mercurial. 3) git2rdata is a useful tool in a reproducible and traceable workflow. vignette("workflow", package = "git2rdata") gives a toy example. 4) vignette("efficiency", package = "git2rdata") provides some insight into the efficiency of file storage, git repository size and speed for writing and reading.
Maintained by Thierry Onkelinx. Last updated 2 months ago.
reproducible-researchversion-control
99 stars 10.03 score 216 scripts 4 dependents
bxc147
Epi:Statistical Analysis in Epidemiology
Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data. In particular representation, manipulation, rate estimation and simulation for multistate data - the Lexis suite of functions, which includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. Contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data and some useful functions for tabulation and plotting, as well as a number of epidemiological data sets.
Maintained by Bendix Carstensen. Last updated 3 months ago.
4 stars 9.64 score 708 scripts 11 dependents
daattali
ddpcr:Analysis and Visualization of Droplet Digital PCR in R and on the Web
An interface to explore, analyze, and visualize droplet digital PCR (ddPCR) data in R. This is the first non-proprietary software for analyzing two-channel ddPCR data. An interactive tool was also created and is available online to facilitate this analysis for anyone who is not comfortable with using R.
Maintained by Dean Attali. Last updated 1 years ago.
61 stars 9.54 score 131 scripts 2 dependents
terminological
dtrackr:Track your Data Pipelines
Track and document 'dplyr' data pipelines. As you filter, mutate, and join your way through a data set, 'dtrackr' seamlessly keeps track of your data flow and makes publication ready documentation of a data pipeline simple.
Maintained by Robert Challen. Last updated 5 months ago.
69 stars 8.78 score 362 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.
65 stars 8.65 score 128 scripts
pablo14
funModeling:Exploratory Data Analysis and Data Preparation Tool-Box
Around 10% of almost any predictive modeling project is spent in predictive modeling, 'funModeling' and the book Data Science Live Book (<https://livebook.datascienceheroes.com/>) are intended to cover remaining 90%: data preparation, profiling, selecting best variables 'dataViz', assessing model performance and other functions.
Maintained by Pablo Casas. Last updated 2 years ago.
100 stars 8.51 score 654 scripts
jranke
mkin:Kinetic Evaluation of Chemical Degradation Data
Calculation routines based on the FOCUS Kinetics Report (2006, 2014). Includes a function for conveniently defining differential equation models, model solution based on eigenvalues if possible or using numerical solvers. If a C compiler (on windows: 'Rtools') is installed, differential equation models are solved using automatically generated C functions. Non-constant errors can be taken into account using variance by variable or two-component error models <doi:10.3390/environments6120124>. Hierarchical degradation models can be fitted using nonlinear mixed-effects model packages as a back end <doi:10.3390/environments8080071>. Please note that no warranty is implied for correctness of results or fitness for a particular purpose.
Maintained by Johannes Ranke. Last updated 1 months ago.
degradationfocus-kineticskinetic-modelskineticsodeode-model
11 stars 8.18 score 78 scripts 1 dependents
uscbiostats
slurmR:A Lightweight Wrapper for 'Slurm'
'Slurm', Simple Linux Utility for Resource Management <https://slurm.schedmd.com/>, is a popular 'Linux' based software used to schedule jobs in 'HPC' (High Performance Computing) clusters. This R package provides a specialized lightweight wrapper of 'Slurm' with a syntax similar to that found in the 'parallel' R package. The package also includes a method for creating socket cluster objects spanning multiple nodes that can be used with the 'parallel' package.
Maintained by George Vega Yon. Last updated 1 years ago.
60 stars 8.07 score 216 scripts 1 dependents
ajschumacher
rjstat:Handle 'JSON-stat' Format in R
Handle 'JSON-stat' format (<https://json-stat.org>) in R. Not all features are supported, especially the extensive metadata features of 'JSON-stat'.
Maintained by Aaron Schumacher. Last updated 2 years ago.
32 stars 6.71 score 179 scripts 3 dependents
johndharrison
seleniumPipes:R Client Implementing the W3C WebDriver Specification
The W3C WebDriver specification defines a way for out-of-process programs to remotely instruct the behaviour of web browsers. It is detailed at <https://w3c.github.io/webdriver/webdriver-spec.html>. This package provides an R client implementing the W3C specification.
Maintained by John Harrison. Last updated 8 years ago.
54 stars 6.66 score 168 scriptsbioc
qcmetrics:A Framework for Quality Control
The package provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats.
Maintained by Laurent Gatto. Last updated 5 months ago.
immunooncologysoftwarequalitycontrolproteomicsmicroarraymassspectrometryvisualizationreportwriting
2 stars 6.03 score 2 dependents
soumyaray
result:Result Type for Safely Handling Operations that can Succeed or Fail
Allows wrapping values in success() and failure() types to capture the result of operations, along with any status codes. Risky expressions can be wrapped in as_result() and functions wrapped in result() to catch errors and assign the relevant result types. Monadic functions can be bound together as pipelines or transaction scripts using then_try(), to gracefully handle errors at any step.
Maintained by Soumya Ray. Last updated 1 years ago.
4 stars 5.14 score 692 scripts
alphaprime7
normfluodbf:Cleans and Normalizes FLUOstar DBF and DAT Files from 'Liposome' Flux Assays
Cleans and Normalizes FLUOstar DBF and DAT Files obtained from liposome flux assays. Users should verify extended usage of the package on files from other assay types.
Maintained by Tingwei Adeck. Last updated 5 months ago.
1 stars 4.98 score 12 scriptsbioc
BiocBook:Write, containerize, publish and version Quarto books with Bioconductor
A BiocBook can be created by authors (e.g. R developers, but also scientists, teachers, communicators, ...) who wish to 1) write (compile a body of biological and/or bioinformatics knowledge), 2) containerize (provide Docker images to reproduce the examples illustrated in the compendium), 3) publish (deploy an online book to disseminate the compendium), and 4) version (automatically generate specific online book versions and Docker images for specific Bioconductor releases).
Maintained by Jacques Serizay. Last updated 5 months ago.
infrastructurereportwritingsoftware
3 stars 4.48 score 4 scripts
data-cleaning
deducorrect:Deductive Correction, Deductive Imputation, and Deterministic Correction
A collection of methods for automated data cleaning where all actions are logged. NOTE: active development has moved to the 'deductive' package.
Maintained by Mark van der Loo. Last updated 10 months ago.
9 stars 4.18 score 34 scripts
vineetbansal
pyMTurkR:A Client for the 'MTurk' Requester API
Provides access to the latest 'Amazon Mechanical Turk' ('MTurk') <https://www.mturk.com> Requester API (version '2017–01–17'), replacing the now deprecated 'MTurkR' package.
Maintained by Vineet Bansal. Last updated 3 years ago.
3.78 score 7 scripts 1 dependentsbioc
Streamer:Enabling stream processing of large files
Large data files can be difficult to work with in R, where data generally resides in memory. This package encourages a style of programming where data is 'streamed' from disk into R via a `producer' and through a series of `consumers' that, typically reduce the original data to a manageable size. The package provides useful Producer and Consumer stream components for operations such as data input, sampling, indexing, and transformation; see package?Streamer for details.
Maintained by Martin Morgan. Last updated 5 months ago.
3.30 score 2 scripts
inbo
n2kanalysis:Generic Functions to Analyse Data from the 'Natura 2000' Monitoring
All generic functions and classes for the analysis for the 'Natura 2000' monitoring. The classes contain all required data and definitions to fit the model without the need to access other sources. Potentially they might need access to one or more parent objects. An aggregation object might for example need the result of an imputation object. The actual definition of the analysis, using these generic function and classes, is defined in dedictated analysis R packages for every monitoring scheme. For example 'abvanalysis' and 'watervogelanalysis'.
Maintained by Thierry Onkelinx. Last updated 2 months ago.
1 stars 3.18 score 7 scripts
bergsmat
wrangle:A Systematic Data Wrangling Idiom
Supports systematic scrutiny, modification, and integration of data. The function status() counts rows that have missing values in grouping columns (returned by na() ), have non-unique combinations of grouping columns (returned by dup() ), and that are not locally sorted (returned by unsorted() ). Functions enumerate() and itemize() give sorted unique combinations of columns, with or without occurrence counts, respectively. Function ignore() drops columns in x that are present in y, and informative() drops columns in x that are entirely NA; constant() returns values that are constant, given a key. Data that have defined unique combinations of grouping values behave more predictably during merge operations.
Maintained by Tim Bergsma. Last updated 5 months ago.
2 stars 2.91 score 41 scripts
tomba-io
tomba:Official R Library for Tomba Email Finder
Email Finder R Client Library. Search emails are based on the website You give one domain name and it returns all the email addresses found on the internet. Email Finder generates or retrieves the most likely email address from a domain name, a first name and a last name. Email verify checks the deliverability of a given email address, verifies if it has been found in our database, and returns their sources.
Maintained by Abedrahim Ben rebia. Last updated 2 years ago.
emailemail-validationemail-verification
2.70 score
kpatera
EVI:Epidemic Volatility Index as an Early-Warning Tool
This is an R package implementing the epidemic volatility index (EVI), as discussed by Kostoulas et. al. (2021) and variations by Pateras et. al. (2023). EVI is a new, conceptually simple, early warning tool for oncoming epidemic waves. EVI is based on the volatility of newly reported cases per unit of time, ideally per day, and issues an early warning when the volatility change rate exceeds a threshold.
Maintained by Konstantinos Pateras. Last updated 1 years ago.
2.70 score 7 scripts
sellorm
rspmapi:R Wrapper Around The RStudio Package Manager API
Provides functions for querying the RStudio Package Manager API. If your oraganisation uses RStudio Packaeg Manager, this package will allow you to interact with it's API directly from R without having to construct the queries manually.
Maintained by Mark Sellors. Last updated 3 years ago.
3 stars 2.18 score 4 scripts
cran
ocd:High-Dimensional Multiscale Online Changepoint Detection
Implements the algorithm in Chen, Wang and Samworth (2020) <arxiv:2003.03668> for online detection of sudden mean changes in a sequence of high-dimensional observations. It also implements methods by Mei (2010) <doi:10.1093/biomet/asq010>, Xie and Siegmund (2013) <doi:10.1214/13-AOS1094> and Chan (2017) <doi:10.1214/17-AOS1546>.
Maintained by Yudong Chen. Last updated 4 years ago.
1.70 score
quinsun
smoke:Small Molecule Octet/BLI Kinetics Experiment
Bio-Layer Interferometry (BLI) is a technology to determine the binding kinetics between biomolecules. BLI signals are small and noisy when small molecules are investigated as ligands (analytes). We develop this package to process and analyze the BLI data acquired on Octet Red96 from Fortebio more accurately. Sun Q., Li X., et al (2020) <doi:10.1038/s41467-019-14238-3>. In this new version, we organize the BLI experiment data and analysis methods into a S4 class with self-explaining structure.
Maintained by Qingan Sun. Last updated 1 years ago.
1.00 score