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Code for RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding

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RSVP

Code for RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding .

Code and tutorial

The R notebook RSVP_Example.ipynb contains R code to implement both RSVP and RSVP-sub. The notebook shows how to:

  • 1 Implement RSVP and RSVP-sub in R;
  • 2 Estimate a graph by ranking the entries of the estimated covariance matrix;
  • 3 Use it in combination with neighbourhood selection to estimate an undirected graphical model.

Application code and dataset

The "GTEX data analysis" section of RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding describes an application of RSVP to gene expression data generated by the GTEX consortium. The DataAnalysis folder contains more information on how to reproduce the results of the paper.

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