I am looking for software (preferably an R package) that can accept a matrix of gene expression values from a time course experiment and then compute a possible gene regulatory network based on the data.
Also I'm looking at aracne2, Califano lab. But would like to try several options.
I am looking for the same answers. The following is the results of my literature review:
First, three review papers should be checked:
According to the review paper, several packages are available currently for construct transcription regulatory network from time series expression data:
Hope this will help you. Any suggestions on this topic are welcome!
Try this: http://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/Rpackages/WGCNA/
Thanks! Any others that infer causal relationships from time series data? (Horvath package seems more general, focused on co-expression networks.)
For this case, you need to perform correlation analysis and use of any test statistics (eg. z test) to identify significant co regulation. For this case, you need large sample size (> 10) for reliable result.
Hi, did you tried RTN package?
ARACNE is pretty good
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