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parmigene--a parallel R package for mutual information estimation and gene network reconstruction
Gabriele Sales1, Chiara Romualdi
1Department of Statistical Sciences, University of Padova, 35121 Padova, Italy.
Bioinformatics (Oxford, England)
|May 3, 2011
Summary
Parmigene, a new R package, reconstructs gene regulatory networks using a minimally biased mutual information estimator. It offers more precise results with significantly reduced computational costs compared to existing software.
Area of Science:
- Bioinformatics
- Computational Biology
- Systems Biology
Background:
- Mutual information is effective for inferring large transcriptional networks.
- Existing methods suffer from biased estimators and high computational costs for large gene sets.
Purpose of the Study:
- Introduce parmigene, an R package designed to overcome limitations in gene network reconstruction.
- Provide a computationally efficient and less biased approach for inferring gene regulatory networks.
Main Methods:
- Implemented a mutual information estimator based on k-nearest neighbor distances.
- Utilized a parallel computing paradigm for network reconstruction.
- Developed as an R package available on CRAN.
Main Results:
- Parmigene demonstrates minimally biased mutual information estimation.
- Achieved significantly reduced computational costs compared to existing software.
- Showed more precise gene network reconstruction results on both in silico and real data.
Conclusions:
- Parmigene offers an improved solution for gene regulatory network inference.
- The package addresses key challenges of bias and computational expense in the field.
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