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 | |
 Pipeline Environment | |
| Developer(s) | Samuel Hobel |
|---|---|
| Stable release | 7.0.3
/ March 3, 2020 |
| Written in | Java |
| Operating system | Linux, Mac OS X, Microsoft Windows |
| Type | Scientific workflow system, Workflow processing environments |
| License | LONI License |
| Website | pipeline |
The LONI Pipeline is a free distributed system for designing, executing, monitoring and sharing scientific workflows[1][2] on grid computing architectures. Pipeline allows users to connect and run any number of different software tools, and conveniently visualize and download the results.
Unlike other workflow processing environments, Pipeline does not require new tools and services to include or be built against the core Pipeline libraries. The Pipeline environment references all data, services and tools as external objects. This allows the Pipeline to run as a light-weight middleware, but at the same time, restrict the scope of its applications. For example, the Pipeline does not provide a set of internal core libraries, filters, and processes for rudimentary image processing (e.g., image addition). All tools necessary to complete an analysis protocol must first be built as external stand-alone applications or services, whose interface methods are then described in the Pipeline XML language. Users can connect to the LONI Cranium server to gain quick access to a wide array of pre-built software applications, such as FSL, AFNI, and FreeSurfer already described in XML as modules and workflows. Pipeline allows users to create new workflow descriptions, edit existing ones, and share their work with others.
Typical pipeline server installations include a suite of core resources that are available to all users with access to the specific server, however, different servers will have different suites of default module and module-group (pipeline) definitions. The previous release (version 5) of the LONI Pipeline[3] provided a mechanism for integrating heterogeneous and incongruous data including images, clinical charts and demographic meta-data.
The LONI Pipeline has hundreds of users in a variety of fields (e.g., genomics,[4] neuro-imaging,[5] and Biomedical Informatics[6]) from academic institutions around the world.
- ^ Rex, D. E., Ma, J.Q., and Toga, A.W. (2003). "The LONI Pipeline Processing Environment." Neuroimage, 19(3), 1033-48.
- ^ Rex, D. E., Shattuck, D. W., Woods, R. P., Narr, K. L., Luders, E., Rehm, K., Stolzner, S. E., Rottenberg, D. E., and Toga, A. W. (2004). "A meta-algorithm for brain extraction in MRI." NeuroImage, 23(2), 625–637
- ^ Dinov ID, Lozev K, Petrosyan P, Liu Z, Eggert P, Pierce, J, Zamanyan, A, Chakrapani, S, Van Horn, JD, Parker, DS, Magsipoc, R, Leung, K, Gutman, B, Woods, RP, Toga, AW. (2010). "Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline." PLoS ONE 5(9): e13070. doi:10.1371/journal.pone.0013070.
- ^ Torri, F., Dinov, ID, Zamanyan, A, Hobel, S, Genco, A, Petrosyan, P, Clark, AP, Liu, Z, Eggert, P, Pierce, J, Knowles, JA, Ames, J, Kesselman, C, Toga, AW, Potkin, SG, Vawter, MP, Macciardi, F. (2012) Next Generation Sequence Analysis and Computational Genomics Using Graphical Pipeline Workflows, Genes, 3(3):545-575; doi:10.3390/genes3030545.
- ^ Woo MS, Dinov, ID, Hobel, S, Zamanyan, A, Choi, YC, Thompson, PM, Toga, AW and Alzheimer’s Disease Neuroimaging Initiative (ADNI) (2015) Structural Brain Changes in Early-Onset Alzheimer’s Disease Subjects Using the LONI Pipeline Environment. Journal of Neuroimaging., in press. DOI: 10.1111/jon.12252
- ^ Toga, WA, Dinov, ID. (2015) Sharing big biomedical data. Journal of Big Data., 2(7):1-12. DOI: 10.1186/s40537-015-0016-1.