G3 talk rld_2
0 likes253 views
This document discusses tools for improving reproducibility in research, including hosting data in GigaDB, sharing images using OMERO, implementing workflows using Galaxy and executable documents, and sharing virtual machines. It emphasizes the need for publishers to host and curate research objects like data, code, and workflows and provide citations for reproducible research. Key tools highlighted are GigaDB for data hosting, OMERO for image hosting, Galaxy for implementing workflows, and virtual machines for sharing full computational environments.
G3 talk rld_2
- 1. Tools for: Open-Source Open-Data Rob L Davidson about.me/rob.davidson
- 2. The problem reproducibility.cs.arizona.edu • 515 papers (429 conf, 86 journal) • <30% reproducible
- 4. The Cause • Stodden 2010 – 638 registrant at NIPS • 30% share code • 20% share data http://web.stanford.edu/~vcs/papers/SMPRCS2010.pdf
- 5. Publishers must provide! Hosting Curating Citations for everything: data, tools + workflows
- 6. Tools for Reproducibility • Data: GigaDB • Images: OMERO • Workflows – Galaxy – Executable Docs – VMs
- 9. Hosting all research objects
- 10. Impact for research objects • Host • Curate • Share • Cite - DOI
- 11. Even more accessible, transparent data? Hosting image data with OMERO
- 12. Hosting Images • Image LIMS • Web embedding – View online, no need for software • Full res • Link all images to publication – No cherry picking http://www.openmicroscopy.org/site/products/omero
- 14. Accessible Cyber-Centipede images OMERO: providing access to imaging data View, filter, measure raw images with direct links from journal article. See all image data, not just cherry picked examples. Download and reprocess.
- 16. The alternative... ...look but don't touch
- 17. Workflows 1. Galaxy galaxyproject.org
- 19. Implement workflows in a community-accepted format http://galaxyproject.org Open source Over 45,000 main Galaxy server users Over 1,000 papers citing Galaxy use Over 55 Galaxy servers deployed
- 20. Implement workflows in an intuitive format Tool list ToCoolp yprigahrt aNBmAFe-Bte 2r0i1s3ation Results panel
- 23. Birmingham Metabo-Galaxy Tools wrapped in Python and XML User sees web form (easy!) Data stored centrally (secure!) Work done centrally (easy update)
- 26. Hosting Workflows 1) Test data 2) Software files 3) Instructions + Galaxy implementation
- 27. Can we reproduce results? SOAPdenovo2 S. aureus pipeline
- 28. Workflows 2. Executable Docs
- 29. Open lab books, dynamic documents • Facilitate reuse and sharing with tools like: Knitr, Sweave, iPython Notebook Sweave • Working towards executable papers…
- 30. E.g.
- 31. E.g.
- 32. Some testimonials for Knitr Authors (Wolfgang Huber) “I do all my projects in Knitr. Having the textual explanation, the associated code and the results all in one place really increases productivity, and helps explaining my analyses to colleagues, or even just to my future self.” Reviewers (Christophe Pouzat) “It took me a couple of hours to get the data, the few custom developed routines, the “vignette” and to REPRODUCE EXACTLY the analysis presented in the manuscript. With few more hours, I was able to modify the authors’ code to change their Fig. 4. In addition to making the presented research trustworthy, the reproducible research paradigm definitely makes the reviewer’s job much more fun!
- 34. Why VMs? • OS settings • Dependencies – Versions – e.g. python! • Data + Code linked • Download or run in cloud
- 35. VMs in GigaDB
- 36. Summary
- 37. Share data in GigaDB Share all images in GigaDB -View images via OMERO Share code in GigaDB! Share pipeline using: Executable docs! Galaxy! VMs!
- 38. Improve reproducibility! Give us data, papers & pipelines* Contact us: scott@gigasciencejournal.com editorial@gigasciencejournal.com database@gigasciencejournal.com * APC’s currently generously covered by BGI until 2015 www.gigasciencejournal.com
- 39. Thanks to: team: Our collaborators: Case study: Ruibang Luo (BGI/HKU) Shaoguang Liang (BGI-SZ) Tin-Lap Lee (CUHK) Qiong Luo (HKUST) Senghong Wang (HKUST) Yan Zhou (HKUST) Funding from: CBIIT @gigascience facebook.com/GigaScience blogs.biomedcentral.com/gigablog/ Peter Li Huayan Gao Chris Hunter Jesse Si Zhe Nicole Nogoy Laurie Goodman Amye Kenall (BMC) Marco Roos (LUMC) Mark Thompson (LUMC) Jun Zhao (Lancaster) Susanna Sansone (Oxford) Philippe Rocca-Serra (Oxford) Alejandra Gonzalez-Beltran (Oxford) www.gigadb.org galaxy.cbiit.cuhk.edu.hk www.gigasciencejournal.com