LONI Pipeline

The LONI Pipeline is a visual language  programming environment  for study designs and data provenance based on complex graphical  workflows. The construction, validation and dissemination of study designs via the  LONI Pipeline uses advanced neuroimaging protocols analyzing  multi-subject and multidimensional data.

To  provide an extensible framework for interoperability of distributed resources,  the LONI Pipeline employs a decentralized infrastructure, where data,  tools and services are linked via an external inter-resource mediating  layer. No modifications of the existing resources are necessary  for their integration with other computational counterparts. The  Pipeline eXtensible Markup Language (XML) schema forms the backbone for  the inter-resource mediating layer. Each XML resource description  includes important information about the resource location, the proper  invocation protocol (i.e., input/output types, parameter specifications,  etc.), run-time controls and data-types. This XML schema also includes  auxiliary metadata about the resource state, specifications, history,  authorship, licensing, and bibliography. The LONI Pipeline  infrastructure facilitates the integration of disparate resources and provides a natural and comprehensive data provenance.  It also enables the broad dissemination of resource metadata  descriptions via web-services and the constructive utilization of  multidisciplinary expertise by experts, novice users and trainees.

Authors

Ivo Dinov
Petros Petrosyan
Zhizhong Liu
Jonathan Pierce
Arthur Toga

Associated Institutions

UCLA

Application Domains
  • Biology
  • Clinical
  • Domain independent
Other Resource Type
Software Subtype
  • Bioinformatics
  • Data mining/Machine learning
  • Document/information retrieval
  • Image analysis
  • NLP / information extraction
  • Query tools/business intelligence
Programming Languages
  • Java
  • Other
Operating Systems
  • Linux
  • OS X
  • Unix
  • Windows
Included Components
  • Application Programming Interface
  • Graphical User Interface
  • Library of modular components
  • Pipeline workflow
  • Plug-in to other software
Dataset Subtype
Data Model Subtype
  • Object oriented
  • Relational
  • Warehouse (star or schema)
Online Resource Subtype
Knowledge Base Subtype
  • Ontology
Intended User Types
  • Clinician
  • Clinical researcher
  • Informatics researcher
  • NLP researcher or developer
  • Software developer
Citations
  • 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
  • Dinov I, Van Horn JD, Lozev KM, Magsipoc R, Petrosyan P, Liu Z, MacKenzie-Graham A, Eggert P, Parker DS and Toga AW (2009) Efficient, Distributed and Interactive Neuroimaging Data Analysis using the LONI Pipeline. Front. Neuroinform., 3(22):1-10. doi:10.3389/neuro.11.022.2009.
  • Rex, DE, Ma, JQ, and Toga, AW. (2003) The LONI Pipeline Processing Environment. Neuroimage, 19(3): 1033-48. doi:10.1016/S1053-8119(03)00185-X.
Available Documentation
  • API
  • Included demo/tutorial data
  • PDF documentation
  • Screenshots
  • Text/pictures
  • Tutorial
  • Video
  • Video demonstration
  • Web page/HTML documentation
Development Milestones

Array Job Submission

The Pipeline server now supports array job submission via JGDI plugin. Array job improves the total processing time of a workflow by combining repeated jobs into one job. Everything is transparent to the users, with individual job’s output and error logs displayed as before. The total processing time on workflows with large number of instances will be improved dramatically.

User Management

User management is supported for Pipeline server. Once enabled, user’s job slot allocation will be based on the number of free slots on submission time and percentage allowed per user. This value is dynamically calculated and updated. User will also be able to monitor their own usage by clicking the server status label on the lower right corner.

XNAT Database

Pipeline now supports XNAT database. Collections on any XNAT server can be integrated as a module with output, by providing an XNAT catalog file and your XNAT credential. The module can be connected to any input processing modules. When executing, the compute nodes will download the data, convert to desired file type and proceed into the subsequent module. For more information, please refer to user guide – XNAT.

Server Configuration Tool

Server configuration tool lets Pipeline server administrators easily configure Pipeline server’s preferences. The tool includes all the preferences required and provides brief description for each field. It has five categories, General, Grid, Access, Packages and Advanced.

MPI and Special Queue Support

Pipeline server supports MPI for SGE and a special queue with external network access enabled. With server support, user can right click on module and under Execution tab’s Advanced Options, provide MPI parameters or check the checkbox to enable external network access queue.

 

Date of Latest Version