AnVILWorkflow: A runnable workflow package for Cloud-implemented bioinformatics analysis pipelines [version 1; peer review: awaiting peer review]
Advancements in sequencing technologies and the development of new data collection methods produce large volumes of biological data. The Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a cloud-based platform for democratizing access to large-scale genomics da...
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| Vydáno v: | F1000 research Ročník 13; s. 1257 |
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| Hlavní autoři: | , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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F1000 Research Limited
2024
F1000 Research Ltd |
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| ISSN: | 2046-1402, 2046-1402 |
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| Abstract | Advancements in sequencing technologies and the development of new data collection methods produce large volumes of biological data. The Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a cloud-based platform for democratizing access to large-scale genomics data and analysis tools. However, utilizing the full capabilities of AnVIL can be challenging for researchers without extensive bioinformatics expertise, especially for executing complex workflows. We present the
AnVILWorkflow R package, which enables the convenient execution of bioinformatics workflows hosted on AnVIL directly from an R environment.
AnVILWorkflow simplifies the setup of the cloud computing environment, input data formatting, workflow submission, and retrieval of results through intuitive functions. We demonstrate the utility of
AnVILWorkflow for three use cases: bulk RNA-seq analysis with
Salmon, metagenomics analysis with
bioBakery, and digital pathology image processing with
PathML. The key features of
AnVILWorkflow include user-friendly browsing of available data and workflows, seamless integration of R and non-R tools within a reproducible analysis pipeline, and accessibility to scalable computing resources without direct management overhead.
AnVILWorkflow lowers the barrier to utilizing AnVIL's resources, especially for exploratory analyses or bulk processing with established workflows. This empowers a broader community of researchers to leverage the latest genomics tools and datasets using familiar R syntax. This package is distributed through the Bioconductor project (
https://bioconductor.org/packages/AnVILWorkflow), and the source code is available through GitHub (
https://github.com/shbrief/AnVILWorkflow). |
|---|---|
| AbstractList | Advancements in sequencing technologies and the development of new data collection methods produce large volumes of biological data. The Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a cloud-based platform for democratizing access to large-scale genomics data and analysis tools. However, utilizing the full capabilities of AnVIL can be challenging for researchers without extensive bioinformatics expertise, especially for executing complex workflows. We present the AnVILWorkflow R package, which enables the convenient execution of bioinformatics workflows hosted on AnVIL directly from an R environment. AnVILWorkflow simplifies the setup of the cloud computing environment, input data formatting, workflow submission, and retrieval of results through intuitive functions. We demonstrate the utility of AnVILWorkflow for three use cases: bulk RNA-seq analysis with Salmon, metagenomics analysis with bioBakery, and digital pathology image processing with PathML. The key features of AnVILWorkflow include user-friendly browsing of available data and workflows, seamless integration of R and non-R tools within a reproducible analysis pipeline, and accessibility to scalable computing resources without direct management overhead. AnVILWorkflow lowers the barrier to utilizing AnVIL's resources, especially for exploratory analyses or bulk processing with established workflows. This empowers a broader community of researchers to leverage the latest genomics tools and datasets using familiar R syntax. This package is distributed through the Bioconductor project ( https://bioconductor.org/packages/AnVILWorkflow), and the source code is available through GitHub ( https://github.com/shbrief/AnVILWorkflow).Advancements in sequencing technologies and the development of new data collection methods produce large volumes of biological data. The Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a cloud-based platform for democratizing access to large-scale genomics data and analysis tools. However, utilizing the full capabilities of AnVIL can be challenging for researchers without extensive bioinformatics expertise, especially for executing complex workflows. We present the AnVILWorkflow R package, which enables the convenient execution of bioinformatics workflows hosted on AnVIL directly from an R environment. AnVILWorkflow simplifies the setup of the cloud computing environment, input data formatting, workflow submission, and retrieval of results through intuitive functions. We demonstrate the utility of AnVILWorkflow for three use cases: bulk RNA-seq analysis with Salmon, metagenomics analysis with bioBakery, and digital pathology image processing with PathML. The key features of AnVILWorkflow include user-friendly browsing of available data and workflows, seamless integration of R and non-R tools within a reproducible analysis pipeline, and accessibility to scalable computing resources without direct management overhead. AnVILWorkflow lowers the barrier to utilizing AnVIL's resources, especially for exploratory analyses or bulk processing with established workflows. This empowers a broader community of researchers to leverage the latest genomics tools and datasets using familiar R syntax. This package is distributed through the Bioconductor project ( https://bioconductor.org/packages/AnVILWorkflow), and the source code is available through GitHub ( https://github.com/shbrief/AnVILWorkflow). Advancements in sequencing technologies and the development of new data collection methods produce large volumes of biological data. The Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a cloud-based platform for democratizing access to large-scale genomics data and analysis tools. However, utilizing the full capabilities of AnVIL can be challenging for researchers without extensive bioinformatics expertise, especially for executing complex workflows. We present the AnVILWorkflow R package, which enables the convenient execution of bioinformatics workflows hosted on AnVIL directly from an R environment. AnVILWorkflow simplifies the setup of the cloud computing environment, input data formatting, workflow submission, and retrieval of results through intuitive functions. We demonstrate the utility of AnVILWorkflow for three use cases: bulk RNA-seq analysis with Salmon, metagenomics analysis with bioBakery, and digital pathology image processing with PathML. The key features of AnVILWorkflow include user-friendly browsing of available data and workflows, seamless integration of R and non-R tools within a reproducible analysis pipeline, and accessibility to scalable computing resources without direct management overhead. AnVILWorkflow lowers the barrier to utilizing AnVIL's resources, especially for exploratory analyses or bulk processing with established workflows. This empowers a broader community of researchers to leverage the latest genomics tools and datasets using familiar R syntax. This package is distributed through the Bioconductor project ( https://bioconductor.org/packages/AnVILWorkflow), and the source code is available through GitHub ( https://github.com/shbrief/AnVILWorkflow). Advancements in sequencing technologies and the development of new data collection methods produce large volumes of biological data. The Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a cloud-based platform for democratizing access to large-scale genomics data and analysis tools. However, utilizing the full capabilities of AnVIL can be challenging for researchers without extensive bioinformatics expertise, especially for executing complex workflows. We present the AnVILWorkflow R package, which enables the convenient execution of bioinformatics workflows hosted on AnVIL directly from an R environment. AnVILWorkflow simplifies the setup of the cloud computing environment, input data formatting, workflow submission, and retrieval of results through intuitive functions. We demonstrate the utility of AnVILWorkflow for three use cases: bulk RNA-seq analysis with Salmon, metagenomics analysis with bioBakery, and digital pathology image processing with PathML. The key features of AnVILWorkflow include user-friendly browsing of available data and workflows, seamless integration of R and non-R tools within a reproducible analysis pipeline, and accessibility to scalable computing resources without direct management overhead. AnVILWorkflow lowers the barrier to utilizing AnVIL’s resources, especially for exploratory analyses or bulk processing with established workflows. This empowers a broader community of researchers to leverage the latest genomics tools and datasets using familiar R syntax. This package is distributed through the Bioconductor project (https://bioconductor.org/packages/AnVILWorkflow), and the source code is available through GitHub (https://github.com/shbrief/AnVILWorkflow). Advancements in sequencing technologies and the development of new data collection methods produce large volumes of biological data. The Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a cloud-based platform for democratizing access to large-scale genomics data and analysis tools. However, utilizing the full capabilities of AnVIL can be challenging for researchers without extensive bioinformatics expertise, especially for executing complex workflows. We present the R package, which enables the convenient execution of bioinformatics workflows hosted on AnVIL directly from an R environment. simplifies the setup of the cloud computing environment, input data formatting, workflow submission, and retrieval of results through intuitive functions. We demonstrate the utility of for three use cases: bulk RNA-seq analysis with , metagenomics analysis with , and digital pathology image processing with The key features of include user-friendly browsing of available data and workflows, seamless integration of R and non-R tools within a reproducible analysis pipeline, and accessibility to scalable computing resources without direct management overhead. lowers the barrier to utilizing AnVIL's resources, especially for exploratory analyses or bulk processing with established workflows. This empowers a broader community of researchers to leverage the latest genomics tools and datasets using familiar R syntax. This package is distributed through the Bioconductor project ( https://bioconductor.org/packages/AnVILWorkflow), and the source code is available through GitHub ( https://github.com/shbrief/AnVILWorkflow). Advancements in sequencing technologies and the development of new data collection methods produce large volumes of biological data. The Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a cloud-based platform for democratizing access to large-scale genomics data and analysis tools. However, utilizing the full capabilities of AnVIL can be challenging for researchers without extensive bioinformatics expertise, especially for executing complex workflows. We present the AnVILWorkflow R package, which enables the convenient execution of bioinformatics workflows hosted on AnVIL directly from an R environment. AnVILWorkflow simplifies the setup of the cloud computing environment, input data formatting, workflow submission, and retrieval of results through intuitive functions. We demonstrate the utility of AnVILWorkflow for three use cases: bulk RNA-seq analysis with Salmon , metagenomics analysis with bioBakery , and digital pathology image processing with PathML. The key features of AnVILWorkflow include user-friendly browsing of available data and workflows, seamless integration of R and non-R tools within a reproducible analysis pipeline, and accessibility to scalable computing resources without direct management overhead. AnVILWorkflow lowers the barrier to utilizing AnVIL’s resources, especially for exploratory analyses or bulk processing with established workflows. This empowers a broader community of researchers to leverage the latest genomics tools and datasets using familiar R syntax. This package is distributed through the Bioconductor project (https://bioconductor.org/packages/AnVILWorkflow), and the source code is available through GitHub (https://github.com/shbrief/AnVILWorkflow). |
| Author | Carey, Vincent Gravel-Pucillo, Kai Davis, Sean Waldron, Levi Ramos, Marcel Schatz, Michael C. Oh, Sehyun Morgan, Martin |
| Author_xml | – sequence: 1 givenname: Sehyun surname: Oh fullname: Oh, Sehyun email: Sehyun.Oh@sph.cuny.edu organization: Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, New York, USA – sequence: 2 givenname: Kai surname: Gravel-Pucillo fullname: Gravel-Pucillo, Kai organization: Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, New York, USA – sequence: 3 givenname: Marcel surname: Ramos fullname: Ramos, Marcel organization: Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, New York, USA – sequence: 4 givenname: Michael C. surname: Schatz fullname: Schatz, Michael C. organization: Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA – sequence: 5 givenname: Sean surname: Davis fullname: Davis, Sean organization: Departments of Biomedical Informatics and Medicine,, University of Colorado Anschutz School of Medicine, Denver, Colorado, USA – sequence: 6 givenname: Vincent orcidid: 0000-0003-4046-0063 surname: Carey fullname: Carey, Vincent organization: Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA – sequence: 7 givenname: Martin surname: Morgan fullname: Morgan, Martin organization: Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA – sequence: 8 givenname: Levi orcidid: 0000-0003-2725-0694 surname: Waldron fullname: Waldron, Levi organization: Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, New York, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39669685$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1093/nar/gkab346 10.1093/bioinformatics/btx617 10.1371/journal.pcbi.1003285 10.7554/eLife.65088 10.5281/zenodo.13868810 10.1093/bioinformatics/btx754 10.1038/nmeth.4197 10.6084/M9.FIGSHARE.27018421.V3 10.1158/1541-7786.MCR-21-0665 10.7490/f1000research.1114631.1 |
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| Copyright | Copyright: © 2024 Oh S et al. Copyright: © 2024 Oh S et al. 2024 |
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| References | M Schatz (ref1) 2022; 2 ref12 ref11 R Patro (ref8) 2017; 14 G Sandve (ref4) 2013; 9 D Yuen (ref5) 2021; 49 L McIver (ref9) 2018; 34 N Weber (ref16) 2018; 34 J Rosenthal (ref10) 2022; 20 ref19 F Beghini (ref15) 2021; 10 K Voss (ref13) 2017 L Hughes (ref7) 2019; 37 ref6 S Oh (ref20) 2024 S Oh (ref18) 2024 38798429 - Res Sq. 2024 May 15:rs.3.rs-4370115. doi: 10.21203/rs.3.rs-4370115/v1 |
| References_xml | – ident: ref6 article-title: (Github). – volume: 49 start-page: W624-W632 year: 2021 ident: ref5 article-title: The Dockstore: enhancing a community platform for sharing reproducible and accessible computational protocols. publication-title: Nucleic Acids Res. doi: 10.1093/nar/gkab346 – ident: ref19 article-title: ENA Browser. – volume: 34 start-page: 1411-1413 year: 2018 ident: ref16 article-title: Nephele: a cloud platform for simplified, standardized and reproducible microbiome data analysis. publication-title: Bioinformatics. doi: 10.1093/bioinformatics/btx617 – volume: 9 start-page: e1003285 year: 2013 ident: ref4 article-title: simple rules for reproducible computational research. publication-title: PLoS Comput. Biol. doi: 10.1371/journal.pcbi.1003285 – volume: 37 start-page: e18094-e18094 year: 2019 ident: ref7 article-title: Harmonization of clinical data across Gen3 data commons. publication-title: J. Clin. Orthod. – volume: 10 year: 2021 ident: ref15 article-title: Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. publication-title: elife. doi: 10.7554/eLife.65088 – year: 2024 ident: ref20 article-title: AnVILWorkflow. publication-title: Zenodo. doi: 10.5281/zenodo.13868810 – volume: 34 start-page: 1235-1237 year: 2018 ident: ref9 article-title: bioBakery: a meta’omic analysis environment. publication-title: Bioinformatics. doi: 10.1093/bioinformatics/btx754 – volume: 14 start-page: 417-419 year: 2017 ident: ref8 article-title: Salmon provides fast and bias-aware quantification of transcript expression. publication-title: Nat. Methods. doi: 10.1038/nmeth.4197 – ident: ref12 article-title: How much did my workflow cost? Terra Support. – volume: 2 year: 2022 ident: ref1 article-title: Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space. publication-title: Cell Genom. – ident: ref11 article-title: Google Cloud. – year: 2024 ident: ref18 article-title: Test datasets for the AnVILWorkflow package. publication-title: figshare. doi: 10.6084/M9.FIGSHARE.27018421.V3 – volume: 20 start-page: 202-206 year: 2022 ident: ref10 article-title: Building Tools for Machine Learning and Artificial Intelligence in Cancer Research: Best Practices and a Case Study with the PathML Toolkit for Computational Pathology. publication-title: Mol. Cancer Res. doi: 10.1158/1541-7786.MCR-21-0665 – year: 2017 ident: ref13 article-title: Full-stack genomics pipelining with GATK4 + WDL + Cromwell. doi: 10.7490/f1000research.1114631.1 – reference: 38798429 - Res Sq. 2024 May 15:rs.3.rs-4370115. doi: 10.21203/rs.3.rs-4370115/v1 |
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| SubjectTerms | AnVIL Cloud Computing Computational Biology - methods eng Genomics Genomics - methods Humans R/Bioconductor Software Software Tool Workflow Workflows |
| Title | AnVILWorkflow: A runnable workflow package for Cloud-implemented bioinformatics analysis pipelines [version 1; peer review: awaiting peer review] |
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