Institute for Computational Genomic Medicine and Institute of Cardiovascular Regeneration, Goethe University Frankfurt am Main, Hessen, Germany.
Methods Mol Biol. 2025;2856:341-356. doi: 10.1007/978-1-0716-4136-1_21.
To reveal gene regulation mechanisms, it is essential to understand the role of regulatory elements, which are possibly distant from gene promoters. Integrative analysis of epigenetic and transcriptomic data can be used to gain insights into gene-expression regulation in specific phenotypes. Here, we discuss STITCHIT, an approach to dissect epigenetic variation in a gene-specific manner across many samples for the identification of regulatory elements without relying on peak calling algorithms. The obtained genomic regions are then further refined using a regularized linear model approach, which can also be used to predict gene expression. We illustrate the use of STITCHIT using H3k27ac ChIP-seq and RNA-seq data from the International Human Epigenome Consortium (IHEC).
为了揭示基因调控机制，了解调控元件的作用至关重要，而这些元件可能远离基因启动子。对表观遗传学和转录组学数据进行综合分析可以帮助我们深入了解特定表型中的基因表达调控。在这里，我们讨论了 STITCHIT，这是一种无需依赖峰调用算法即可在许多样本中以特定于基因的方式解析表观遗传变异以识别调控元件的方法。然后，使用正则化线性模型方法进一步细化获得的基因组区域，该方法也可用于预测基因表达。我们使用来自国际人类表观基因组联合会（IHEC）的 H3k27ac ChIP-seq 和 RNA-seq 数据说明了 STITCHIT 的使用。
