Paulsen Martina
Life Sciences, Saarland University, Saarbrücken, Germany.
Methods Mol Biol. 2012;925:251-62. doi: 10.1007/978-1-62703-011-3_17.
Computational studies on imprinted genes can have very different purposes: one major aim of these studies is the identification of DNA elements that distinguish imprinted genes from biallelically expressed genes. Comparative studies may help to identify imprinting regulatory elements and to understand common mechanisms of imprinted gene regulation in mammalian species. To date, the continuously growing number of genomic and epigenetic data sets makes detailed, genome-wide analyses on imprinted genes feasible. However, imprinted genes are characterized by genomic features that can influence statistics and can make such studies difficult. Hence, comparative computational studies can get very complex and require a tight interaction between bioinformaticians and biologists. Furthermore, analyses of raw data that are generated by micro-array hybridization and high-throughput sequencing technologies require computational approaches that have been designed especially for the epigenetic field. This chapter gives an overview about databases and software that is suitable for analyses of imprinted genes. Furthermore, possible difficulties that are typical for computational and statistical analyses of imprinted genes are described.
这些研究的一个主要目标是识别将印记基因与双等位基因表达基因区分开来的DNA元件。比较研究可能有助于识别印记调控元件，并了解哺乳动物物种中印记基因调控的共同机制。迄今为止，基因组和表观遗传数据集的不断增加使得对印记基因进行详细的全基因组分析成为可能。然而，印记基因具有可影响统计数据并使此类研究变得困难的基因组特征。因此，比较计算研究可能会变得非常复杂，需要生物信息学家和生物学家之间紧密互动。此外，对通过微阵列杂交和高通量测序技术生成的原始数据进行分析需要专门为表观遗传领域设计的计算方法。本章概述了适用于分析印记基因的数据库和软件。此外，还描述了印记基因计算和统计分析中典型的可能困难。
