PCIT | R Documentation |

The PCIT algorithm is used for reconstruction of gene co-expression networks (GCN) that combines the concept partial correlation coefficient with information theory to identify significant gene to gene associations defining edges in the reconstruction of GCN.

PCIT(input, tolType = "mean")

`input` |
A correlation matrix. |

`tolType` |
Type of tolerance (default: 'mean') given the 3 pairwise correlations
(see |

Returns an list with the significant correlations, raw adjacency matrix and significant adjacency matrix.

REVERTER, Antonio; CHAN, Eva KF. Combining partial correlation and an information theory approach to the reversed engineering of gene co-expression networks. Bioinformatics, v. 24, n. 21, p. 2491-2497, 2008. https://academic.oup.com/bioinformatics/article/24/21/2491/192682

# loading a simulated normalized data data('simNorm') # getting the PCIT results for first 30 genes results <- PCIT(simNorm[1:30, ]) # printing PCIT output first 15 rows head(results$tab, 15)

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