ImpulseDE: Detection of differentially expressed genes in time series data using impulse models

Jil Sander, Joachim L Schultze, Nir Yosef

Research output: Contribution to journalArticlepeer-review

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, wedemon- strate its power to represent underlying biology of gene expression in microarray and RNA-Seq data.

Original languageEnglish
Pages (from-to)757-759
Number of pages3
JournalBioinformatics
Volume33
Issue number5
Early online date2 Dec 2016
DOIs
StatePublished - 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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