A new R package for network-based biomarker discovery released

A new R package, netClass, has been release. netClass integrate network information, such as protein-protein interaction network or KEGG, to mRNA classification, but also incorporate miRNA to mRNA with mi-mRNA interaction network for biomarker discovery. This methods we called stSVM and already published in PloS ONE (Cun et al 2013). Apart from stSVM, we also implement the flowing methods in netClass: 

  1. AEP (average gene expression of pathway), Guo et al., BMC Bioinformatics 2005, 6:58.
  2. PAC (pathway activitive classification), Lee E, et  al., PLoS Comput Biol 4(11): e1000217.
  3. hubc (Hub nodes classification), Taylor et al.(2009) Nat. Biotech.: doi: 10.1038/nbt.152
  4. frSVM (filter via top ranked genes), Cun et al. arXiv:1212.3214 ;  Winter etal., PLoS Comput Biol 8(5): e1002511.
  5. stSVM (network smoothed t-statistic) , Cun et al., PloS One,.

NetClass can be download from souceforg ( http://sourceforge.net/projects/netclassr/) or , CRAN (http://cran.r-project.org/web/packages/netClass/ ). For more detail of netClass, you can refer these four papers:

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About Y. Cun

Computational biologist
此条目发表在Computational Genomics, Machine Learning, Medicine Genomics, Programming, R分类目录,贴了, 标签。将固定链接加入收藏夹。

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