Researchers at National Taiwan Ocean University and National Tsing Hua University, Taiwan proposed a workflow which integrated annotations from KEGG biological pathways and Gene Ontology associations for manipulating multiple RNA-seq datasets. The developed system started from mapping short reads onto reference genes, and then performed normalization procedures on read coverage to evaluate and compare expression levels within various gene clusters. Different levels of gene expression were indicated by diverse color shades and graphically shown in designed temporal pathways. Representative GO terms associated with differentially expressed gene cluster were also visually displayed by a GO tag cloud representation. Three different public RNA-Seq datasets were applied to demonstrate that the proposed workflow could provide effective and efficient analysis on differential gene expression for either cross-strain comparison or an identical sample sequenced at different time points.
- Chen CM, Shih TH, Pai TW, Liu ZL, Chang MD. (2012) RNA-seq Coverage Effects on Biological Pathways and GO Tag Clouds. 2012 IEEE 6th International Conference on Systems Biology (ISB). [article]