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PCIT: an R package for weighted gene co-expression networks based on partial correlation and information theory
Nathan S Watson-Haigh1, Haja N Kadarmideen, Antonio Reverter
1CSIRO Livestock Industries, Queensland Bioscience Precinct, St Lucia, QLD 4067, Australia. nathan.watson-haigh@csiro.au
Bioinformatics (Oxford, England)
|December 17, 2009
Summary
The PCIT algorithm, for detecting gene-gene associations in co-expression networks, is now an R package. This package offers portable scripts for parallel and non-parallel computing environments.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Gene-gene associations are crucial for understanding biological pathways.
- Co-expression network analysis is a common method for inferring these associations.
- Existing algorithms may lack portability or ease of use.
Purpose of the Study:
- To provide a user-friendly R package for the PCIT algorithm.
- To facilitate the detection of meaningful gene-gene associations.
- To ensure script portability across different computing environments.
Main Methods:
- The PCIT algorithm was implemented in the R programming language.
- Automatic detection of parallel environments was incorporated into the package.
- The R package is available for download from CRAN.
Main Results:
- The PCIT algorithm is now accessible as a portable R package.
- Scripts function seamlessly in both parallel and non-parallel environments.
- The package supports Linux and MS Windows operating systems.
Conclusions:
- The PCIT R package simplifies the analysis of gene-gene associations.
- Enhanced portability increases the algorithm's accessibility and usability.
- This tool aids researchers in co-expression network analysis.
