The targets R package: a dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing

Landau, Will

doi:10.21105/joss.02959

Cited by 142 publications

(93 citation statements)

References 3 publications

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“…The lack of integration between notebooks and pipeline frameworks can create friction during the analysis process, which can discourage users from using them jointly. Efforts such as NoWorkflow/YesWorkflow and internal frameworks such as Targets 238 are helping to bridge these distinctions, but few solutions have sought to aid notebook-pipeline integration in general.…”

Section: Discussionmentioning

confidence: 99%

The role of metadata in reproducible computational research

et al. 2021

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Summary Reproducible computational research (RCR) is the keystone of the scientific method for in silico analyses, packaging the transformation of raw data to published results. In addition to its role in research integrity, improving the reproducibility of scientific studies can accelerate evaluation and reuse. This potential and wide support for the FAIR principles have motivated interest in metadata standards supporting reproducibility. Metadata provide context and provenance to raw data and methods and are essential to both discovery and validation. Despite this shared connection with scientific data, few studies have explicitly described how metadata enable reproducible computational research. This review employs a functional content analysis to identify metadata standards that support reproducibility across an analytic stack consisting of input data, tools, notebooks, pipelines, and publications. Our review provides background context, explores gaps, and discovers component trends of embeddedness and methodology weight from which we derive recommendations for future work.

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Section: Discussionmentioning

confidence: 99%

The role of metadata in reproducible computational research

et al. 2021

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“…A Docker image is available to run the code at https://hub.docker.com/r/joelnitta/ moorea_filmies. The 'targets' package (Landau 2021)…”

Section: Discussionmentioning

confidence: 99%

“…Code used to analyze the data and generate figures and this manuscript are available on GitHub (https://github.com/joelnitta/moorea_filmies).A Docker image is available to run the code at https://hub.docker.com/r/joelnitta/ moorea_filmies. The 'targets' package(Landau 2021) was used to automate the workflow. The 'ggplot2' (Wickham 2016), 'ggtree',(Yu et al 2017) and 'patchwork'(https://github.com/thomasp85/patchwork) packages were used to generate the figures.…”

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confidence: 99%

Ecophysiological differentiation between life stages in filmy ferns (Hymenophyllaceae)

Nitta

Watkins

Holbrook

et al. 2021

Preprint

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Desiccation tolerance was a key trait that allowed plants to colonize land. However, little is known about the transition from desiccation tolerant non-vascular plants to desiccation sensitive vascular ones. Filmy ferns (Hymenophyllaceae) represent a useful system to investigate how water-stress strategies differ between non-vascular and vascular stages within a single organism because they have vascularized sporophytes and nonvascular gametophytes that are each capable of varying degrees of desiccation tolerance. To explore this, we surveyed sporophytes and gametophytes of 19 species (22 taxa including varieties) of filmy ferns on Moorea (French Polynesia) and used chlorophyll fluorescence to measure desiccation tolerance and light responses. We conducted phylogenetically informed analyses to identify differences in physiology between life stages and growth habits. Gametophytes had similar or less desiccation tolerance (ability to recover from 2 d desiccation at -86 MPa) and lower photosynthetic optima (maximum electron transport rate of photosystem II and light level at 95% of that rate) than sporophytes. Epiphytes were more tolerant of desiccation than terrestrial species in both generations. Despite their lack of greater physiological tolerances, gametophytes of several species occurred over a wider elevational range than conspecific sporophytes. Our results demonstrate that filmy fern gametophytes and sporophytes differ in their physiology and niche requirements, and point to the importance of microhabitat in shaping the evolution of water-use strategies in vascular plants.

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“…Python package dependencies were found using the Wheelodex API [63] and the johnnydep package (v1.8) [64]. All of the data acquisition and analysis was organised using a targets (v0.4.2) [65] pipeline with dependencies managed using renv (v0.13.2) [54].…”

Section: Methodsmentioning

confidence: 99%

Over 1000 tools reveal trends in the single-cell RNA-seq analysis landscape

Zappia

Theis

2021

Preprint

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Recent years have seen a revolution in single-cell technologies, particularly single-cell RNA-sequencing (scRNA-seq). As the number, size and complexity of scRNA-seq datasets continue to increase, so does the number of computational methods and software tools for extracting meaning from them. Since 2016 the scRNA-tools database has catalogued software tools for analysing scRNA-seq data. With the number of tools in the database passing 1000, we take this opportunity to provide an update on the state of the project and the field. Analysis of five years of analysis tool tracking data clearly shows the evolution of the field, and that the focus of developers has moved from ordering cells on continuous trajectories to integrating multiple samples and making use of reference datasets. We also find evidence that open science practices reward developers with increased recognition and help accelerate the field.

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The targets R package: a dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing

Cited by 142 publications

References 3 publications

The role of metadata in reproducible computational research

The role of metadata in reproducible computational research

Ecophysiological differentiation between life stages in filmy ferns (Hymenophyllaceae)

Over 1000 tools reveal trends in the single-cell RNA-seq analysis landscape

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