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/).
Supplementary data are available at Bioinformatics online.
