PCIT-package

PCIT


	This package provides the necessary functions for performing the
	Partial Correlation coefficient with Information Theory (PCIT) algorithm
	developed by Reverter and Chan (2008). The PCIT algorithm identifies
	meaningful correlations to define edges in a weighted network.
	
	The algorithm can be applied to any correlation-based network including but
	not limited to gene co-expression networks.


 package

Apply Partial Correlation coefficient with Information
Theory (PCIT) to a correlation matrix.
The PCIT algorithm identifies meaningful correlations to define
edges in a weighted network. The algorithm can be applied to
any correlation-based network including but not limited to gene
co-expression networks.
To reduce compute time by making use of multiple compute cores,
simply run PCIT on a computer with has multiple cores and also
has the Rmpi package installed. PCIT will then auto-detect the
multicore environment and run in parallel mode without the need
to rewrite your scripts. This makes scripts, using PCIT, portable
across single core (or no Rmpi package installed) computers
which will run in serial mode and multicore (with Rmpi package
installed) computers which will run in parallel mode.

PCIT-package: Partial Correlation coefficient with Information Theory (PCIT)

Description

Arguments

Details

References