Carey V J, Gentleman R
Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave., Boston, MA 02115, USA.
Pac Symp Biocomput. 2009:380-90. doi: 10.1142/9789812836939_0036.
Several influential studies of genotypic determinants of gene expression in humans have now been published based on various populations including HapMap cohorts. The magnitude of the analytic task (transcriptome vs. SNP-genome) is a hindrance to dissemination of efficient, thorough, and auditable inference methods for this project. We describe the structure and use of Bioconductor facilities for inference in genetics of gene expression, with simultaneous application to multiple HapMap cohorts. Tools distributed for this purpose are readily adapted for the structure and analysis of privately-generated data in expression genetics.
目前已经发表了几项关于人类基因表达的基因型决定因素的有影响力的研究，这些研究基于包括HapMap队列在内的各种人群。分析任务的规模（转录组与单核苷酸多态性基因组）阻碍了为该项目传播高效、全面且可审计的推理方法。我们描述了用于基因表达遗传学推理的Bioconductor工具的结构和用途，并同时应用于多个HapMap队列。为此目的分发的工具很容易适用于表达遗传学中私人生成数据的结构和分析。
