Cheung Hoi-Hung, Claus Janek, Singh Sumeeta, Sastry Chandan, Rennert Owen M, Chan Wai-Yee, Lee Tin-Lap
Laboratory of Clinical and Developmental Genomics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
Methods Mol Biol. 2013;1067:225-33. doi: 10.1007/978-1-62703-607-8_14.
The recent revolution of genomics techniques has allowed the detection of various sequence features and biological variations on whole-genome scale. However, these high-resolution data present significant challenges for experimental biologists to understand and analyze. The conventional way is to use genome browsers to locate and visualize regions of interest. But it lacks user-friendly data mining functionality. Here we present a protocol that allows rapid annotation of genomic coordinate data by using TileMapper. Interesting biological annotations from large-scale genomic data, such as transcriptome analysis, chromatin immunoprecipitation on chip, or methyl-DNA immunoprecipitation (MeDIP) studies generated from the tiling microarrays and other platforms, could be analyzed without requiring computational skills. The outputs are saved in tabulated format, which permit flexible and simple processing in spreadsheet software, or to be exported to other pipelines for subsequent analysis.
近期基因组学技术的变革使得在全基因组规模上检测各种序列特征和生物学变异成为可能。然而，这些高分辨率数据给实验生物学家的理解和分析带来了重大挑战。传统方法是使用基因组浏览器来定位和可视化感兴趣的区域。但它缺乏用户友好的数据挖掘功能。在此，我们提出一种协议，该协议允许使用TileMapper对基因组坐标数据进行快速注释。来自大规模基因组数据的有趣生物学注释，如转录组分析、芯片染色质免疫沉淀或来自平铺微阵列和其他平台的甲基化DNA免疫沉淀（MeDIP）研究，无需计算技能即可进行分析。输出结果以表格形式保存，这使得在电子表格软件中进行灵活简单的处理成为可能，或者可以导出到其他管道进行后续分析。
