Leveraging the CEDAR Workbench for ontology-linked submission of AIRR data to the NCBI-SRA

Presenting Author Information 

Name

Syed Ahmad Chan Bukhari

Institution

Department of Pathology, Yale School of Medicine, New Haven, CT, USA

PI

Steven H Kleinstein

Email

ahmad.chan@yale.edu

Phone Number

2034155487

Additional Author Information 

Names and affiliations of additional authors (one per line)

Kei-Hoi Cheung, Department of Emergency Medicine; Yale Center for Medical Informatics, Yale University School of Medicine, New Haven, CT, USA.
Martin J. O'Connor, Center for Expanded Data Annotation and Retrieval, Stanford Center for Biomedical Informatics Research
John Graybeal, Center for Expanded Data Annotation and Retrieval, Stanford Center for Biomedical Informatics Research
Mark A. Musen Center for Expanded Data Annotation and Retrieval, Stanford Center for Biomedical Informatics Research
Steven H. Kleinstein, Department of Pathology, Yale School of Medicine, New Haven, CT, USA.

Is there an additional contact person?

Yes

Name of additional contact

Steven H Kleinstein

Email address of additional contact

steven.kleinstein@yale.edu

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Abstract Information

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Abstract Title

Leveraging the CEDAR Workbench for ontology-linked submission of AIRR data to the NCBI-SRA

Abstract Description

Next-generation sequencing technologies have led to a rapid production of high-throughput sequence data characterizing adaptive immune-receptor repertoires (AIRRs). As part of the AIRR community (http://airr.irmacs.sfu.ca) data standards working group, we have developed an initial set of metadata recommendations for publishing AIRR sequencing studies. These recommendations will be implemented in several public repositories, including the NCBI sequence read archive (SRA). Submissions to SRA typically use a flat-file template and include only a minimal amount of term validation. In order to ease the metadata authoring and to implement the ontological terms validation of repertoire sequence data, we are developing an interactive template through CEDAR workbench that will allow for ontological validation, and subsequent deposition in SRA. CEDAR workbench also allows the user to populate the template with metadata for data submission to various data repositories. The incorporation of template-element level ontology mapping not only facilitates validation of data submission, but also enables intelligent queries within and across repositories.