Relevant background literature

[dhimmel]

This issue is for commenting with relevant literature or prior work. For substantive discussion about a prior work, consider opening a new issue.

[dhimmel]

Here are several works I'm aware of on the topic of network permutation. Created the markdown using the following manubot cite command:

manubot cite --render --format=markdown\
   doi:10.1137/1.9781611972795.67 doi:10.15363/thinklab.d178 doi:10.1093/bioinformatics/btu474 doi:10.1186/s12859-016-1402-1 arxiv:cond-mat/0312028

1. Randomization Techniques for Graphs
   Sami Hanhijärvi, Gemma C. Garriga, Kai Puolamäki
   Proceedings of the 2009 SIAM International Conference on Data Mining (2009-04-30) https://doi.org/f3mn58
   DOI: 10.1137/1.9781611972795.67

2. Assessing the effectiveness of our hetnet permutations
   Daniel Himmelstein
   ThinkLab (2016-02-25) https://doi.org/f3mqt5
   DOI: 10.15363/thinklab.d178

3. Fast randomization of large genomic datasets while preserving alteration counts
   Andrea Gobbi, Francesco Iorio, Kevin J. Dawson, David C. Wedge, David Tamborero, Ludmil B. Alexandrov, Nuria Lopez-Bigas, Mathew J. Garnett, Giuseppe Jurman, Julio Saez-Rodriguez
   Bioinformatics (2014-08-22) https://doi.org/f6j9vb
   DOI: 10.1093/bioinformatics/btu474 · PMID: 25161255 · PMCID: PMC4147926

4. Efficient randomization of biological networks while preserving functional characterization of individual nodes
   Francesco Iorio, Marti Bernardo-Faura, Andrea Gobbi, Thomas Cokelaer, Giuseppe Jurman, Julio Saez-Rodriguez
   BMC Bioinformatics (2016-12) https://doi.org/gfkw2z
   DOI: 10.1186/s12859-016-1402-1 · PMID: 27998275 · PMCID: PMC5168876

5. On the uniform generation of random graphs with prescribed degree sequences
   R. Milo, N. Kashtan, S. Itzkovitz, M. E. J. Newman, U. Alon
   arXiv (2003-12-01) https://arxiv.org/abs/cond-mat/0312028v2

[dhimmel]

1. Assessing statistical significance in causal graphs
   Leonid Chindelevitch, Po-Ru Loh, Ahmed Enayetallah, Bonnie Berger, Daniel Ziemek
   BMC Bioinformatics (2012) https://doi.org/f3xbhf
   DOI: 10.1186/1471-2105-13-35 · PMID: 22348444 · PMCID: PMC3307026

One of our Pfizer collaborators mentioned this study on our call. Specifically, the "Causal Graph Randomization" section until the Discussion is relevant.

[dhimmel]

I met @dkoslicki at a Data-Driven Drug Repurposing Workshop. We discussed methods for network permutation that preserve node degree. @dkoslicki mentioned a paper that compared methods. The only method name I remember was WaRSwap (Weighted-and-Reverse-Swap) from:

Sustained-input switches for transcription factors and microRNAs are central building blocks of eukaryotic gene circuits
Molly Megraw, Sayan Mukherjee, Uwe Ohler
Genome Biology (2013) https://doi.org/ghm7hk
DOI: 10.1186/gb-2013-14-8-r85 · PMID: 23972209 · PMCID: PMC4054853

@dkoslicki do you remember the comparison paper you showed me?

[dkoslicki]

Sure! The published version is here though I liked the structure of the preprint (doesn't hide all the math in the supplement).

Always happy to talk further about it