Managing data provenance in genome project workflows

Author

De Paula, Ramon ; Holanda, Maristela T. ; Walter, Maria Emilia M. T. ; Lifschitz, Sergio

Author_Institution

Comput. Sci. Dept., Univ. of Brasilia (UnB), Brasilia, Brazil

fYear

2012

fDate

4-7 Oct. 2012

Firstpage

654

Lastpage

661

Abstract

In this article, we propose the application of the PROV-DM model to manage data provenance for workflows designed to support genome projects. This provenance model aims at storing details of each execution of the workflow, which include raw and produced data, computational tools and versions, parameters, and so on. This way, biologists can review details of a particular workflow execution, compare information generated among different executions, and plan new ones more efficiently. In addition, we have created a provenance simulator to facilitate the inclusion of a provenance data model in genome projects. In order to validate our proposal, we discuss a case study of an RNA-Seq project that aims to identify, measure and compare RNA expression levels across liver and kidney RNA samples produced by high-throughput automatic sequencers.

Keywords

RNA; biology computing; data models; genomics; kidney; liver; PROV-DM model; RNA expression levels; RNA-Seq project; data provenance management; genome project workflows; high-throughput automatic sequencers; kidney RNA; liver; provenance data model; Bioinformatics; Biological system modeling; DNA; Data models; Databases; Genomics; RNA; PROV-DM; bioinformatics; data provenance; genome project; workflow;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine Workshops (BIBMW), 2012 IEEE International Conference on

Conference_Location

Philadelphia, PA

Print_ISBN

978-1-4673-2746-6

Electronic_ISBN

978-1-4673-2744-2

Type

conf

DOI

10.1109/BIBMW.2012.6470215

Filename

6470215