Cargando…
Creating and sharing reproducible research code the workflowr way
Making scientific analyses reproducible, well documented, and easily shareable is crucial to maximizing their impact and ensuring that others can build on them. However, accomplishing these goals is not easy, requiring careful attention to organization, workflow, and familiarity with tools that are...
Autores principales: | Blischak, John D., Carbonetto, Peter, Stephens, Matthew |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6833990/ https://www.ncbi.nlm.nih.gov/pubmed/31723427 http://dx.doi.org/10.12688/f1000research.20843.1 |
Ejemplares similares
-
DataPackageR: Reproducible data preprocessing, standardization and sharing using R/Bioconductor for collaborative data analysis
por: Finak, Greg, et al.
Publicado: (2018) -
Knowledge sharing and discovery across heterogeneous research infrastructures
por: Farshidi, Siamak, et al.
Publicado: (2023) -
DataUp: A tool to help researchers describe and share tabular data
por: Strasser, Carly, et al.
Publicado: (2014) -
Arkas: Rapid reproducible RNAseq analysis
por: Colombo, Anthony R., et al.
Publicado: (2017) -
Increasing workflow development speed and reproducibility with Vectools
por: Weirick, Tyler, et al.
Publicado: (2018)