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 language | English |
|---|---|
| Pages (from-to) | 757-759 |
| Number of pages | 3 |
| Journal | Bioinformatics |
| Volume | 33 |
| Issue number | 5 |
| Early online date | 2 Dec 2016 |
| DOIs | |
| State | Published - 2017 |
| Externally published | Yes |
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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