R packages for gene regulatory networks from time series data
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7.6 years ago
Ann ★ 2.3k

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.

RNA-Seq ChIP-Seq R • 5.3k views
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Also I'm looking at aracne2, Califano lab. But would like to try several options.

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6.7 years ago
pengchy ▴ 450

I am looking for the same answers. The following is the results of my literature review:

First, three review papers should be checked:

  • Lopes, M. and G. Bontempi (2013). "Experimental assessment of static and dynamic algorithms for gene regulation inference from time series expression data." Front Genet 4: 303.
  • Kim, Y., et al. (2014). "Inference of dynamic networks using time-course data." Brief Bioinform 15(2): 212-228.
  • Liu, Z. P. (2015). "Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data." Curr Genomics 16(1): 3-22.

According to the review paper, several packages are available currently for construct transcription regulatory network from time series expression data:

  • GRNInfer, Huber group LASSO, these two can construct the regulatory network from multiple time series expression data.
  • TDARACNE, DPC.
  • Bayes network: Banjo, BNFinder, GlobalMIT
  • TESLA
  • KELLER
  • ARTIVA

Hope this will help you. Any suggestions on this topic are welcome!

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Thanks! Any others that infer causal relationships from time series data? (Horvath package seems more general, focused on co-expression networks.)

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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.

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6.7 years ago

Hi, did you tried RTN package?

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6.7 years ago
joram • 0

ARACNE is pretty good

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