Showing 22 of total 22 results (show query)
ropensci
tarchetypes:Archetypes for Targets
Function-oriented Make-like declarative pipelines for Statistics and data science are supported in the 'targets' R package. As an extension to 'targets', the 'tarchetypes' package provides convenient user-side functions to make 'targets' easier to use. By establishing reusable archetypes for common kinds of targets and pipelines, these functions help express complicated reproducible pipelines concisely and compactly. The methods in this package were influenced by the 'targets' R package. by Will Landau (2018) <doi:10.21105/joss.00550>.
Maintained by William Michael Landau. Last updated 4 days ago.
data-sciencehigh-performance-computingpeer-reviewedpipeliner-targetopiareproducibilitytargetsworkflow
142 stars 11.27 score 1.7k scripts 10 dependentsropensci
jagstargets:Targets for JAGS Pipelines
Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the 'jagstargets' R package is leverages 'targets' and 'R2jags' to ease this burden. 'jagstargets' makes it super easy to set up scalable JAGS pipelines that automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom code is required, and there is no need to manually configure branching, so usage is much easier than 'targets' alone. For the underlying methodology, please refer to the documentation of 'targets' <doi:10.21105/joss.02959> and 'JAGS' (Plummer 2003) <https://www.r-project.org/conferences/DSC-2003/Proceedings/Plummer.pdf>.
Maintained by William Michael Landau. Last updated 4 months ago.
bayesianhigh-performance-computingjagsmaker-targetopiareproducibilityrjagsstatisticstargetscpp
10 stars 6.95 score 32 scriptsropensci
stantargets:Targets for Stan Workflows
Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the 'stantargets' R package leverages 'targets' and 'cmdstanr' to ease these burdens. 'stantargets' makes it super easy to set up scalable Stan pipelines that automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom code is required, and there is no need to manually configure branching, so usage is much easier than 'targets' alone. 'stantargets' can access all of 'cmdstanr''s major algorithms (MCMC, variational Bayes, and optimization) and it supports both single-fit workflows and multi-rep simulation studies. For the statistical methodology, please refer to 'Stan' documentation (Stan Development Team 2020) <https://mc-stan.org/>.
Maintained by William Michael Landau. Last updated 2 months ago.
bayesianhigh-performance-computingmaker-targetopiareproducibilitystanstatisticstargets
49 stars 6.85 score 180 scriptsropensci
geotargets:'Targets' Extensions for Geographic Spatial Formats
Provides extensions for various geographic spatial file formats, such as shape files and rasters. Currently provides support for the 'terra' geographic spatial formats. See the vignettes for worked examples, demonstrations, and explanations of how to use the various package extensions.
Maintained by Nicholas Tierney. Last updated 12 days ago.
geospatialpipeliner-targetopiarasterreproducibilityreproducible-researchtargetsvectorworkflow
73 stars 6.79 score
taxonomicallyinformedannotation
tima:Taxonomically Informed Metabolite Annotation
This package provides the infrastructure to perform Taxonomically Informed Metabolite Annotation.
Maintained by Adriano Rutz. Last updated 1 hours ago.
metabolite annotationchemotaxonomyscoring systemnatural productscomputational metabolomicstaxonomic distancespecialized metabolome
9 stars 6.55 score 32 scripts 2 dependentsropensci
gittargets:Data Version Control for the Targets Package
In computationally demanding data analysis pipelines, the 'targets' R package (2021, <doi:10.21105/joss.02959>) maintains an up-to-date set of results while skipping tasks that do not need to rerun. This process increases speed and increases trust in the final end product. However, it also overwrites old output with new output, and past results disappear by default. To preserve historical output, the 'gittargets' package captures version-controlled snapshots of the data store, and each snapshot links to the underlying commit of the source code. That way, when the user rolls back the code to a previous branch or commit, 'gittargets' can recover the data contemporaneous with that commit so that all targets remain up to date.
Maintained by William Michael Landau. Last updated 9 months ago.
data-sciencedata-version-controldata-versioningreproducibilityreproducible-researchtargetsworkflow
88 stars 5.99 score 11 scripts
adafede
cascade:Contextualizing untargeted Annotation with Semi-quantitative Charged Aerosol Detection for pertinent characterization of natural Extracts
This package provides the infrastructure to perform Automated Composition Assessment of Natural Extracts.
Maintained by Adriano Rutz. Last updated 4 days ago.
metabolite annotationcharged aerosol detectorsemi-quantitativenatural productscomputational metabolomicsspecialized metabolome
2 stars 5.76 score 40 scripts 1 dependents
daranzolin
sqltargets:'Targets' Extension for 'SQL' Queries
Provides an extension for 'SQL' queries as separate file within 'targets' pipelines. The shorthand creates two targets, the query file and the query result.
Maintained by David Ranzolin. Last updated 6 months ago.
39 stars 5.72 score 18 scripts
dipterix
ravedash:Dashboard System for Reproducible Visualization of 'iEEG'
Dashboard system to display the analysis results produced by 'RAVE' (Magnotti J.F., Wang Z., Beauchamp M.S. (2020), Reproducible analysis and visualizations of 'iEEG' <doi:10.1016/j.neuroimage.2020.117341>). Provides infrastructure to integrate customized analysis pipelines into dashboard modules, including file structures, front-end widgets, and event handlers.
Maintained by Zhengjia Wang. Last updated 5 months ago.
1 stars 4.35 score 45 scripts
psychelzh
tarflow.iquizoo:Setup "targets" Workflows for "iquizoo" Data Processing
For "iquizoo" data processing, there is already a package called "preproc.iquizoo", but eventually the use of it is relied on a workflow. This package is used to build such workflows based on tools provided by "targets" package which mimics the logic of "make", automating the building processes.
Maintained by Liang Zhang. Last updated 5 months ago.
10 stars 3.60 score 1 scripts
nyuglobalties
blueprintr:Automagically Document and Test Datasets Using Targets Or Drake
Documents and tests datasets in a reproducible manner so that data lineage is easier to comprehend for small to medium tabular data. Originally designed to aid data cleaning tasks for humanitarian research groups, specifically large-scale longitudinal studies.
Maintained by Patrick Anker. Last updated 9 months ago.
1 stars 3.40 score 7 scripts
tjmahr
notestar:Notebooks Using 'Targets' and 'Bookdown'
'Targets' is an R package for dependency and build management in data analysis projects. This package provides a set of targets and project infrastructure to create 'bookdown'-based notebooks using 'targets'.
Maintained by Tristan Mahr. Last updated 2 months ago.
bookdownknitrpandocrmarkdowntargets
30 stars 3.18 score 7 scripts
mikejohnson51
climateR.catalogs:
A collection of tools for maniputatling hydrologic and hydraulic networks
Maintained by Mike Johnson. Last updated 1 years ago.
16 stars 2.90 score 1 scriptsadafede
sapid:A Strategy to Analyze Plant Extracts Taste In Depth
This package provides the infrastructure to implement a Strategy to Analyze Plant Extracts Taste In Depth.
Maintained by Adriano Rutz. Last updated 5 days ago.
computational metabolomicsnatural extractstaste
2.90 score
owp-spatial
reference.fabric:Hydrological Reference Fabric Tools
Development tools and `targets` pipeline for generating a national hydrological geospatial reference fabric.
Maintained by Justin Singh-Mohudpur. Last updated 2 months ago.
1 stars 2.90 score
nlmixr2
nlmixr2targets:Targets for 'nlmixr2' Pipelines
'nlmixr2' often has long runtimes. A pipeline toolkit tailored to 'nlmixr2' workflows leverages 'targets' and 'nlmixr2' to ease reproducible workflows. 'nlmixr2targets' ensures minimal rework in model development with 'nlmixr2' and 'targets' by simplifying and standardizing models and datasets.
Maintained by Bill Denney. Last updated 1 months ago.
2.70 score 6 scripts
adrientaudiere
greenAlgoR:Compute ecological footprint in R
This package computes ecological footprint in R (based on [green-algorithms](https://calculator.green-algorithms.org/). greenAlgoR also made it simple to compute ecological footprint of \{[targets](https://github.com/ropensci/targets)\} pipelines.
Maintained by Adrien Taudière. Last updated 4 months ago.
1 stars 2.18 score 1 scripts
mps9506
bookdowntargets:Targets for bookdown pipeline
Provides a targets pipeline extension for bookdown projects. For the underlying methodology, please refer to the documentation of 'targets' <doi:10.21105/joss.02959>.
Maintained by Michael Schramm. Last updated 10 months ago.
2.00 score 3 scripts
emptyfield-ds
rrr.workshop:Install Materials for Reproducible Research in R
Install learning materials for Reproducible Research in R.
Maintained by Malcolm Barrett. Last updated 4 years ago.
1.70 score 1 scripts
mhpob
telemetar:Archetypes for Targets and Fish Telemetry
What the package does (one paragraph).
Maintained by Michael OBrien. Last updated 1 years ago.
1.70 score 3 scripts
robitalec
CSEE.reproducible.workflows.workshop:Workshop for CSEE 2023 On Reproducible Workflows In R
Developing a reproducible workflow in R using functions, targets and renv.
Maintained by Alec L. Robitaille. Last updated 2 years ago.
conflictedfunctionsprojectsrenvreproducibilitytargetstargets-pipeline
1 stars 1.70 score