VSEAMS：使用汇总GWAS数据进行变异集富集分析的管道将IKZF3、BATF和ESRRA鉴定为1型糖尿病中的关键转录因子
VSEAMS: A pipeline for variant set enrichment analysis using summary GWAS data identifies IKZF3, BATF and ESRRA as key transcription factors in type 1 diabetes
摘要：
研究动机：全基因组关联研究（GWAS）已经确定了许多与疾病易感性有关的基因座。GWAS汇总统计量（p值）和功能基因组数据集的整合应有助于阐明机制。结果如下：我们描述了一个先前描述的非参数方法，以测试是否GWAS信号富集在功能定义的基因座的情况下，只有GWAS p值是可用的扩展。该方法在VSEAMS中实现，VSEAMS是一个免费的软件管道。我们使用VSEAMS将通过转录因子敲除实验定义的功能基因集与1型糖尿病的GWAS结果整合，并发现与IKZF 3、BATF和ESRRA相关的基因集中的变异集富集。IKZF 3位于已知的T1D易感区域，而BATF和ESRRA与其他免疫疾病易感区域重叠，验证了我们的方法，并提出了1型糖尿病研究的新途径。可用性和实现：VSEAMS可从http://github.com/ollyburren/vseams下载。
英文摘要：
Motivation: Genome-wide association studies (GWAS) have identified many loci implicated in disease susceptibility. Integration of GWAS summary statistics (p values) and functional genomic datasets should help to elucidate mechanisms. Results: We describe the extension of a previously described non-parametric method to test whether GWAS signals are enriched in functionally defined loci to a situation where only GWAS p values are available. The approach is implemented in VSEAMS, a freely available software pipeline. We use VSEAMS to integrate functional gene sets defined via transcription factor knock down experiments with GWAS results for type 1 diabetes and find variant set enrichment in gene sets associated with IKZF3, BATF and ESRRA. IKZF3 lies in a known T1D susceptibility region, whilst BATF and ESRRA overlap other immune disease susceptibility regions, validating our approach and suggesting novel avenues of research for type 1 diabetes. Availability and implementation: VSEAMS is available for download http://github.com/ollyburren/vseams.
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