16(th) IHIW: immunogenomic data-management methods. report from the immunogenomic data analysis working group (IDAWG)

Area of Science:

• Immunogenomics
• Genomics
• Computational Biology

Background:

• Current data management practices in immunogenomics are not well-documented.
• The impact of varying data management approaches on HLA and KIR data analysis is unknown.
• Standardization is needed for consistent analysis and data sharing.

Purpose of the Study:

• To assess current HLA and KIR data generation, management, and analysis practices.
• To identify challenges and opportunities for improving data sharing in immunogenomics.
• To inform the development of community standards for data management and analysis.

Main Methods:

• A 45-question survey was developed and distributed globally.
• Survey covered loci genotyped, typing systems, nomenclature, software, and ambiguity resolution.
• Respondents demonstrated HLA ambiguity resolution with simulated datasets.

Main Results:

• 156 respondents from 35 nations completed the survey by May 2012.
• Survey captured diverse practices in HLA and KIR data handling.
• Respondents represented a broad geographical distribution of the immunogenomic community.

Conclusions:

• The survey provides a snapshot of current immunogenomic data practices.
• Further work is needed to develop community data sharing standards and tools.
• Future efforts will focus on ambiguity resolution documentation, data management tools, and novel analysis methods.