Visualization and clustering of high-dimensional transcriptome data using GATE

Methods Mol Biol. 2014:1150:131-9. doi: 10.1007/978-1-4939-0512-6_7.

Abstract

The potential gains from advances in high-throughput experimental molecular biology techniques are commonly not fully realized since these techniques often produce more data than can be easily organized and visualized. To address these problems, GATE (Grid-Analysis of Time-Series Expression) was developed. GATE is an integrated software platform for the analysis and visualization of high-dimensional time-series datasets, which allows flexible interrogation of time-series data against a wide range of databases of prior knowledge, thus linking observed molecular dynamics to potential genetic, epigenetic, and signaling mechanisms responsible for observed dynamics. This article provides a brief guide to using GATE effectively.

MeSH terms

  • Biostatistics / methods*
  • Cluster Analysis
  • Computer Graphics*
  • Gene Expression Profiling / methods*
  • Software*