Sander Jil, Schultze Joachim L, Yosef Nir
Genomics and Immunoregulation, LIMES-Institute, University of Bonn, Bonn, 53115, Germany.
Single Cell Genomics and Epigenomics Unit at the University of Bonn and the German Center for Neurodegenerative Diseases, Bonn, Germany.
Bioinformatics. 2017 Mar 1;33(5):757-759. doi: 10.1093/bioinformatics/btw665.
Perturbations in the environment lead to distinctive gene expression changes within a cell. Observed over time, those variations can be characterized by single impulse-like progression patterns. ImpulseDE is an R package suited to capture these patterns in high throughput time series datasets. By fitting a representative impulse model to each gene, it reports differentially expressed genes across time points from a single or between two time courses from two experiments. To optimize running time, the code uses clustering and multi-threading. By applying ImpulseDE , we demonstrate its power to represent underlying biology of gene expression in microarray and RNA-Seq data.
ImpulseDE is available on Bioconductor ( https://bioconductor.org/packages/ImpulseDE/ ).
Supplementary data are available at Bioinformatics online.
环境扰动会导致细胞内基因表达发生独特变化。随着时间的推移，这些变化可以通过单一脉冲样的进展模式来表征。ImpulseDE是一个R包，适用于在高通量时间序列数据集中捕捉这些模式。通过为每个基因拟合一个代表性的脉冲模型，它可以报告来自单个时间进程或两个实验的两个时间进程中各时间点的差异表达基因。为了优化运行时间，该代码使用了聚类和多线程技术。通过应用ImpulseDE，我们展示了它在微阵列和RNA测序数据中表征基因表达潜在生物学特性的能力。
ImpulseDE可在Bioconductor上获取（https://bioconductor.org/packages/ImpulseDE/）。
补充数据可在《生物信息学》在线版获取。
