Hollenbach J A, Mack S J, Gourraud P-A, Single R M, Maiers M, Middleton D, Thomson G, Marsh S G E, Varney M D
Center for Genetics, Children's Hospital & Research Center Oakland, Oakland, CA, USA.
Tissue Antigens. 2011 Nov;78(5):333-44. doi: 10.1111/j.1399-0039.2011.01777.x.
Modern high-throughput HLA and KIR typing technologies are generating a wealth of immunogenomic data with the potential to revolutionize the fields of histocompatibility and immune-related disease association and population genetic research, much as SNP-based approaches have revolutionized association research. The STrengthening the REporting of Genetic Association studies (STREGA) statement provides community-based data reporting and analysis standards for genomic disease-association studies, identifying specific areas in which adoption of reporting guidelines can improve the consistent interpretation of genetic studies. While aspects of STREGA can be applied to immunogenomic studies, HLA and KIR research requires additional consideration, as the high levels of polymorphism associated with immunogenomic data pose unique methodological and computational challenges to the synthesis of information across datasets. Here, we outline the principle challenges to consistency in immunogenomic studies, and propose that an immunogenomic-specific analog to the STREGA statement, a STrengthening the REporting of Immunogenomic Studies (STREIS) statement, be developed as part of the 16th International HLA and Immunogenetics Workshop. We propose that STREIS extends at least four of the 22 elements of the STREGA statement to specifically address issues pertinent to immunogenomic data: HLA and KIR nomenclature, data-validation, ambiguity resolution, and the analysis of highly polymorphic genetic systems. As with the STREGA guidelines, the intent behind STREIS is not to dictate the design of immunogenomic studies, but to ensure consistent and transparent reporting of research, facilitating the synthesis of HLA and KIR data across studies.
现代高通量HLA和KIR分型技术正在产生大量免疫基因组数据，这些数据有可能彻底改变组织相容性和免疫相关疾病关联以及群体遗传学研究领域，就像基于单核苷酸多态性（SNP）的方法彻底改变了关联研究一样。加强遗传关联研究报告（STREGA）声明为基因组疾病关联研究提供了基于社区的数据报告和分析标准，确定了采用报告指南可改善遗传研究一致性解释的特定领域。虽然STREGA的某些方面可应用于免疫基因组研究，但HLA和KIR研究需要额外考虑，因为与免疫基因组数据相关的高度多态性给跨数据集信息的综合带来了独特的方法学和计算挑战。在此，我们概述了免疫基因组研究一致性方面的主要挑战，并提议作为第16届国际HLA与免疫遗传学研讨会的一部分，制定一份类似于STREGA声明的免疫基因组学专用声明，即加强免疫基因组研究报告（STREIS）声明。我们提议STREIS扩展STREGA声明22项要素中的至少四项，以专门解决与免疫基因组数据相关的问题：HLA和KIR命名法、数据验证、歧义解决以及高度多态遗传系统的分析。与STREGA指南一样，STREIS背后的意图不是规定免疫基因组研究的设计，而是确保研究报告的一致性和透明度，促进跨研究的HLA和KIR数据的综合。
