Department of Genetics, Stanford University, Stanford, California 94305, USA.
Genome Res. 2012 Sep;22(9):1813-31. doi: 10.1101/gr.136184.111.
Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) has become a valuable and widely used approach for mapping the genomic location of transcription-factor binding and histone modifications in living cells. Despite its widespread use, there are considerable differences in how these experiments are conducted, how the results are scored and evaluated for quality, and how the data and metadata are archived for public use. These practices affect the quality and utility of any global ChIP experiment. Through our experience in performing ChIP-seq experiments, the ENCODE and modENCODE consortia have developed a set of working standards and guidelines for ChIP experiments that are updated routinely. The current guidelines address antibody validation, experimental replication, sequencing depth, data and metadata reporting, and data quality assessment. We discuss how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data. All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals.
染色质免疫沉淀(ChIP)结合高通量 DNA 测序(ChIP-seq)已成为一种用于绘制活细胞中转录因子结合和组蛋白修饰的基因组位置的宝贵且广泛应用的方法。尽管其应用广泛,但这些实验的实施方式、结果评分和质量评估方式以及数据和元数据的归档方式存在相当大的差异,这些差异会影响任何全基因组 ChIP 实验的质量和实用性。通过我们在进行 ChIP-seq 实验方面的经验,ENCODE 和 modENCODE 联盟为 ChIP 实验制定了一套工作标准和指南,并定期进行更新。当前的指南涵盖了抗体验证、实验重复、测序深度、数据和元数据报告以及数据质量评估。我们讨论了以这些方式评估的 ChIP 质量如何影响 ChIP-seq 数据的不同用途。分析中使用的所有数据集都已在 ENCODE(http://encodeproject.org/ENCODE/)和 modENCODE(http://www.modencode.org/)门户上进行了公开查看和下载。