title: ImpulseDE: detection of differentially expressed genes in time series data using impulse models.
abstract: 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/ ).
  
  
  
  niryosef@berkeley.edu.
  
  
  
  Supplementary data are available at Bioinformatics online.
authors: Genomics and Immunoregulation, LIMES-Institute, University of Bonn, Bonn, 53115, Germany.
authors: Jil
authors: J
authors: Sander
authors: 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.
authors: Joachim L
authors: JL
authors: Schultze
authors: Electrical Engineering and Computer Science, Center for Computational Biology, University of California Berkeley, Berkeley, CA 94720-1776, USA.
authors: Nir
authors: N
authors: Yosef
mesh_terms: D000818:Animals; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation; D051379:Mice; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software; D013601:T-Lymphocytes / Q000378:metabolism; D013995:Time