Ten quick tips for building FAIR workflows

de Visser, Casper; Johansson, Lennart F.; Kulkarni, Purva; Mei, Hailiang; Neerincx, Pieter; Joeri van der Velde, K.; Horvatovich, Péter; van Gool, Alain J.; Swertz, Morris A.; Hoen, Peter A. C. ‘t; Niehues, Anna

doi:10.1371/journal.pcbi.1011369

Cited by 16 publications

(7 citation statements)

References 53 publications

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“…The workflow is developed in Snakemake, 17 a widely used workflow language, 15 and follows best practice recommendations for workflow development. 32 Importantly, ZARP relies on publicly available bioinformatics tools that each can be considered state-of-the-art in their specific tool class, 33 and it handles bulk, stranded, single-or paired-ended RNAseq data.…”

Section: Methodsmentioning

confidence: 99%

“…ZARP development follows best practices for scientific analysis workflows. 32 First of all, we chose to develop the workflow in Snakemake, 17 a widely adopted workflow management system 16 that allows for robust and scalable execution of computational analyses. To further enhance reusability and portability of the workflow, i.e., that it can be deployed in various scenarios, such as "on premise" High Performance/Throughput Computing (HPC/HTC) clusters or in the cloud, 51 for each step (referred to as "rule" in Snakemake) of the workflow we have defined both a "rule-specific" Conda environment recipe file and a container image.…”

Section: Development Principles and Best Practicesmentioning

confidence: 99%

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ZARP: A user-friendly and versatile RNA-seq analysis workflow

Katsantoni,

Gypas,

Herrmann

et al. 2024

F1000Res

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Background RNA sequencing (RNA-seq) is a widely used technique in many scientific studies. Given the plethora of models and software packages that have been developed for processing and analyzing RNA-seq datasets, choosing the most appropriate ones is a time-consuming process that requires an in-depth understanding of the data, as well as of the principles and parameters of each tool. In addition, packages designed for individual tasks are developed in different programming languages and have dependencies of various degrees of complexity, which renders their installation and execution challenging for users with limited computational expertise. Workflow languages and execution engines with support for virtualization and encapsulation options such as containers and Conda environments facilitate these tasks considerably. The resulting computational workflows can then be reliably shared with the scientific community, enhancing reusability and the reproducibility of results as individual analysis steps are becoming more transparent and portable. Methods Here we present ZARP, a general purpose RNA-seq analysis workflow that builds on state-of-the-art software in the field to facilitate the analysis of RNA-seq datasets. ZARP is developed in the Snakemake workflow language and can run locally or in a cluster environment, generating extensive reports not only of the data but also of the options utilized. It is built using modern technologies with the ultimate goal to reduce the hands-on time for bioinformaticians and non-expert users and serve as a template for future workflow development. To this end, we also provide ZARP-cli, a dedicated command-line interface that may make running ZARP on an RNA-seq library of interest as easy as executing a single two-word command. Conclusions ZARP is a powerful RNA-seq analysis workflow that is easy to use even for beginners, built using best software development practices, available under a permissive Open Source license and open to contributions by the scientific community.

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Section: Methodsmentioning

confidence: 99%

Section: Development Principles and Best Practicesmentioning

confidence: 99%

ZARP: A user-friendly and versatile RNA-seq analysis workflow

Katsantoni,

Gypas,

Herrmann

et al. 2024

F1000Res

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“…Registration remains notoriously uncommon in space medicine, as is in most scientific fields, except for those that involve randomized controlled trials [13,21] and systematic reviews [17]. However, there have been initiatives and suggestions on improving additional types of studies more frequently, including but not limited to, observational studies [22][23][24][25][26][27], animal studies [20], and mathematical modeling [10,19,28].…”

Section: Plos Onementioning

confidence: 99%

Assessment of transparency indicators in space medicine

Bellomo,

Zavalis,

Ioannidis

2024

PLoS ONE

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Space medicine is a vital discipline with often time-intensive and costly projects and constrained opportunities for studying various elements such as space missions, astronauts, and simulated environments. Moreover, private interests gain increasing influence in this discipline. In scientific disciplines with these features, transparent and rigorous methods are essential. Here, we undertook an evaluation of transparency indicators in publications within the field of space medicine. A meta-epidemiological assessment of PubMed Central Open Access (PMC OA) eligible articles within the field of space medicine was performed for prevalence of code sharing, data sharing, pre-registration, conflicts of interest, and funding. Text mining was performed with the rtransparent text mining algorithms with manual validation of 200 random articles to obtain corrected estimates. Across 1215 included articles, 39 (3%) shared code, 258 (21%) shared data, 10 (1%) were registered, 110 (90%) contained a conflict-of-interest statement, and 1141 (93%) included a funding statement. After manual validation, the corrected estimates for code sharing, data sharing, and registration were 5%, 27%, and 1%, respectively. Data sharing was 32% when limited to original articles and highest in space/parabolic flights (46%). Overall, across space medicine we observed modest rates of data sharing, rare sharing of code and almost non-existent protocol registration. Enhancing transparency in space medicine research is imperative for safeguarding its scientific rigor and reproducibility.

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“…Finally, practices implementing FAIR Principles for Research Software can increase reproducibility of integrative multi-omics analyses (31)(32)(33).…”

Section: Prerequisites For Multi-omics Analysis and Integrationmentioning

confidence: 99%

“…Additionally, intra- and inter-batch QC samples can help identify and adjust for batch effects (30). Finally, practices implementing FAIR Principles for Research Software can increase reproducibility of integrative multi-omics analyses (31–33).…”

Section: Prerequisites For Multi-omics Analysis and Integrationmentioning

confidence: 99%

Multi-omics Quality Assessment in Personalized Medicine through EATRIS

Alonso-Andrés,

Baldazzi,

Chen

et al. 2023

Preprint

Self Cite

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Molecular characterization of a biological sample, e.g., with omics approaches, is fundamental for the development and implementation of personalized and precision medicine approaches. In this context, quality assessment is one of the most critical aspects. Accurate performance and interpretation of omics techniques is based on consensus, harmonization, and standardization of protocols, procedures, data analysis and reference values and materials. EATRIS, the European Infrastructure for Translational Medicine (www.EATRIS.eu), brings together resources and services to support researchers in developing their biomedical discoveries into novel translational tools and interventions for better health outcomes. Here we describe activities of member facilities of EATRIS towards quality assessment of pre-clinical sample processing, clinical omics data generation, multi-omics data integration, and dissemination of the resources in a Multi-Omics Toolbox, the principal deliverable of the EATRIS Plus project for the consolidation of EATRIS towards translational Medicine.

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Ten quick tips for building FAIR workflows

Cited by 16 publications

References 53 publications

ZARP: A user-friendly and versatile RNA-seq analysis workflow

ZARP: A user-friendly and versatile RNA-seq analysis workflow

Assessment of transparency indicators in space medicine

Multi-omics Quality Assessment in Personalized Medicine through EATRIS

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