ArticleF1000Research2017
The Dockstore: enabling modular, community-focused sharing of Docker-based genomics tools and workflows.
Article in F1000Research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
50 citing papers in PubMed.
- Galaxy for accessible, reproducible, and collaborative data analyses: 2026 update.Nucleic acids research · 2026Article
- Warp analysis research pipelines: cloud-optimized workflows for biological data processing and reproducible analysis.Bioinformatics (Oxford, England) · 2025Article
- The BRAIN Initiative data-sharing ecosystem: Characteristics, challenges, benefits, and opportunities.eLife · 2024Article
- Cloud-based large-scale curation of medical imaging data using AI segmentation.Research square · 2024Article
- Phased nanopore assembly with Shasta and modular graph phasing with GFAse.Genome research · 2024Article
- Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows.Viruses · 2024Article
- Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research.Frontiers in genetics · 2024Article
- Challenges and opportunities in sharing microbiome data and analyses.Nature microbiology · 2023Review
- Federated Analysis for Privacy-Preserving Data Sharing: A Technical and Legal Primer.Annual review of genomics and human genetics · 2023Review
- Resources and tools for rare disease variant interpretation.Frontiers in molecular biosciences · 2023Review
- A workflow reproducibility scale for automatic validation of biological interpretation results.GigaScience · 2022Article
- Container Profiler: Profiling resource utilization of containerized big data pipelines.GigaScience · 2022Article
- Workflow sharing with automated metadata validation and test execution to improve the reusability of published workflows.GigaScience · 2022Article
- Opportunities and challenges for the use of common controls in sequencing studies.Nature reviews. Genetics · 2022Review
- IoT cloud laboratory: Internet of Things architecture for cellular biology.Internet of things (Amsterdam, Netherlands) · 2022Article
- The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update.Nucleic acids research · 2022Article
- STAAR workflow: a cloud-based workflow for scalable and reproducible rare variant analysis.Bioinformatics (Oxford, England) · 2022Article
- Narrative online guides for the interpretation of digital-pathology images and tissue-atlas data.Nature biomedical engineering · 2022Review
- A complete pedigree-based graph workflow for rare candidate variant analysis.Genome research · 2022Article
- Federated analysis of BRCA1 and BRCA2 variation in a Japanese cohort.Cell genomics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
As genomic datasets continue to grow, the feasibility of downloading data to a local organization and running analysis on a traditional compute environment is becoming increasingly problematic. Current large-scale projects, such as the ICGC PanCancer Analysis of Whole Genomes (PCAWG), the Data Platform for the U.S. Precision Medicine Initiative, and the NIH Big Data to Knowledge Center for Translational Genomics, are using cloud-based infrastructure to both host and perform analysis across large data sets. In PCAWG, over 5,800 whole human genomes were aligned and variant called across 14 cloud and HPC environments; the processed data was then made available on the cloud for further analysis and sharing. If run locally, an operation at this scale would have monopolized a typical academic data centre for many months, and would have presented major challenges for data storage and distribution. However, this scale is increasingly typical for genomics projects and necessitates a rethink of how analytical tools are packaged and moved to the data. For PCAWG, we embraced the use of highly portable Docker images for encapsulating and sharing complex alignment and variant calling workflows across highly variable environments. While successful, this endeavor revealed a limitation in Docker containers, namely the lack of a standardized way to describe and execute the tools encapsulated inside the container. As a result, we created the Dockstore ( https://dockstore.org), a project that brings together Docker images with standardized, machine-readable ways of describing and running the tools contained within. This service greatly improves the sharing and reuse of genomics tools and promotes interoperability with similar projects through emerging web service standards developed by the Global Alliance for Genomics and Health (GA4GH).
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.