TSGA 1.0

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 

     SupplementaryData

 

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.

 

Citation:

[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.