An R Package for Tissue Specific Genes Analysis
Copyright 2008 ©
Ye Chengyin, Wang Xusheng, Jun Zhu
Institute of Bioinformatics, Zhejiang University, China
TSGA is an R package used for microarray datasets analysis in purpose of identification of genes with overall treatments specificity and detection treatments with specific expression patterns for each gene. It improved ROKU method [1] by adding a gene expression filtration step. This software was written by ye which can be freely obtained from here.
The procedures included in TSGA for microarray data analysis are:
² Corrected Shannon Entropy Calculation for microarray data: the value indicates the overall specificity of each gene
² Specific Expression Patterns Detection, using an outlier detection-based method
² Principle Component Analysis (PCA) for the genes with high overall specificity
² Cluster analysis for genes and treatments
² Plotting for different results from above analysis
This package is suitable for microarray data of one-factor experimental design with multiple treatment levels.
Package and Manual Download
| Vignettes (Documentation) | Package | Downloads |
| TSGA_Manual.pdf | Source | TSGA_1.0.tar.gz |
| Windows binary | TSGA_1.0.zip |
Supplementary Data Download
Error Messages and Troubleshooting:
If you have any questions with our software, please contact Jun Zhu, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310029, China. Email: jzhu@zju.edu.cn.
[1] Kadota K, Ye J, Nakai Y, Terada T, Shimizu K: ROKU: a novel method for identification of tissue-specific genes. BMC Bioinformatics 2006, 7:294.
[2] Ye Chengyin, Wang Xusheng, Jun Zhu: TSGA: an R package for tissue specific genes analysis. submitted.