Universitat Pompeu Fabra, E08003 Barcelona, Spain.
Bioinformatics. 2011 Dec 15;27(24):3333-40. doi: 10.1093/bioinformatics/btr570. Epub 2011 Oct 12.
High-throughput sequencing (HTS) has revolutionized gene regulation studies and is now fundamental for the detection of protein-DNA and protein-RNA binding, as well as for measuring RNA expression. With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing.
We describe Pyicos, a powerful toolkit for the analysis of mapped reads from diverse HTS experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. We prove the effectiveness of Pyicos to select for significant signals and show that its accuracy is comparable and sometimes superior to that of methods specifically designed for each particular type of experiment. Pyicos facilitates the analysis of a variety of HTS datatypes through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics.
Open-source software, with tutorials and protocol files, is available at http://regulatorygenomics.upf.edu/pyicos or as a Galaxy server at http://regulatorygenomics.upf.edu/galaxy
Supplementary data are available at Bioinformatics online.
高通量测序 (HTS) 彻底改变了基因调控研究，现在是检测蛋白质-DNA 和蛋白质-RNA 结合以及测量 RNA 表达的基础。随着 HTS 数据集的种类和测序深度的增加，对更灵活和更节省内存的工具来分析它们的需求也在不断增长。
我们描述了 Pyicos，这是一个用于分析来自各种 HTS 实验（ChIP-Seq，无论是点状还是广泛信号、CLIP-Seq 和 RNA-Seq）的映射读取的强大工具包。我们证明了 Pyicos 选择显著信号的有效性，并表明其准确性可与专门为每种特定类型的实验设计的方法相媲美，有时甚至更优。Pyicos 通过其灵活性和内存效率促进了各种 HTS 数据类型的分析，为将数据集成到调控基因组学模型中提供了有用的框架。
开源软件，带有教程和协议文件，可在 http://regulatorygenomics.upf.edu/pyicos 获得，也可在 http://regulatorygenomics.upf.edu/galaxy 作为 Galaxy 服务器获得。
补充数据可在 Bioinformatics 在线获得。
