Ye Tao, Ravens Sarina, Krebs Arnaud R, Tora Làszlò
Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), UMR 7104 CNRS, UdS, INSERM U964, BP 10142, F-67404 ILLKIRCH Cedex, CU de Strasbourg, France.
Methods Mol Biol. 2014;1150:141-52. doi: 10.1007/978-1-4939-0512-6_8.
Chromatin immunoprecipitation coupled high-throughput sequencing (ChIP-seq) is a common method to study in vivo protein-DNA interactions at the genome-wide level. The processing, analysis, and biological interpretation of gigabyte datasets, generated by several ChIP-seq runs, is a challenging task for biologists. The seqMINER platform has been designed to handle, compare, and visualize different sequencing datasets in a user-friendly way. Different analysis methods are applied to understand common and specific binding patterns of single or multiple datasets to answer complex biological questions. Here, we give a detailed protocol about the different analysis modules implemented in the recent version of seqMINER.
染色质免疫沉淀结合高通量测序（ChIP-seq）是在全基因组水平研究体内蛋白质-DNA相互作用的常用方法。由多次ChIP-seq实验产生的千兆字节数据集的处理、分析和生物学解释，对生物学家来说是一项具有挑战性的任务。seqMINER平台旨在以用户友好的方式处理、比较和可视化不同的测序数据集。应用不同的分析方法来理解单个或多个数据集的共同和特定结合模式，以回答复杂的生物学问题。在这里，我们给出了关于seqMINER最新版本中实现的不同分析模块的详细方案。
