Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
Centre for Epigenetics, University of Copenhagen, Copenhagen, Denmark.
Nat Struct Mol Biol. 2016 Apr;23(4):349-57. doi: 10.1038/nsmb.3180. Epub 2016 Feb 29.
To empower experimentalists with a means for fast and comprehensive chromatin immunoprecipitation sequencing (ChIP-seq) data analyses, we introduce an integrated computational environment, EaSeq. The software combines the exploratory power of genome browsers with an extensive set of interactive and user-friendly tools for genome-wide abstraction and visualization. It enables experimentalists to easily extract information and generate hypotheses from their own data and public genome-wide datasets. For demonstration purposes, we performed meta-analyses of public Polycomb ChIP-seq data and established a new screening approach to analyze more than 900 datasets from mouse embryonic stem cells for factors potentially associated with Polycomb recruitment. EaSeq, which is freely available and works on a standard personal computer, can substantially increase the throughput of many analysis workflows, facilitate transparency and reproducibility by automatically documenting and organizing analyses, and enable a broader group of scientists to gain insights from ChIP-seq data.
为了赋予实验人员快速全面的染色质免疫沉淀测序 (ChIP-seq) 数据分析能力，我们引入了一个集成的计算环境 EaSeq。该软件将基因组浏览器的探索能力与一套广泛的交互式和用户友好的工具相结合，用于全基因组的抽象和可视化。它使实验人员能够轻松地从自己的数据和公共全基因组数据集提取信息并生成假设。为了演示目的，我们对公共多梳 ChIP-seq 数据进行了荟萃分析，并建立了一种新的筛选方法，对来自小鼠胚胎干细胞的 900 多个数据集进行分析，以寻找可能与多梳募集相关的因子。EaSeq 免费提供，可在标准个人计算机上运行，它可以大大提高许多分析工作流程的效率，通过自动记录和组织分析来提高透明度和可重复性，并使更多的科学家能够从 ChIP-seq 数据中获得洞察力。
