This package is used to infer and evaluate first order, secnod order, low order and relevace low ordr partial correlation (RLowPC) from large scale gene expression data. For each pair of genes, the general partial correlation is calculated by removing all the remained controls. However, in large network a number of remained controls may not truely connect to the pair of genes, which are inrrelevant controls. To increase the precision of network predictions, we use RLowPC method to calculated partial correlation by only removing the more relevant controls.
|Author||Wenbin Guo <[email protected]>|
|Maintainer||Wenbin Guo <[email protected]>|
|Package repository||View on GitHub|
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