edgeWeight {PANR} | R Documentation |
This is an internal function to compute edge weights before inferring a posterior association network.
edgeWeight(object, which="bm1", type="SNR", log=TRUE, ...)
object |
an object of S4 class |
which |
a character value specifying which BetaMixture modelling result to use: first-order (if 'bm1') or second-order (if 'bm2'). |
type |
a character value giving the type of edge weight to compute: signal- to-noise ratio (if 'SNR'), posterior probability odd (if 'PPR') or posterior probability (if 'PP'). |
log |
a logical value specifying whether or not to compute logrithms for edge weights. |
This function will be called by infer
to compute edge weights for posterior
association networks. When inferring a signed PAN, signal-to-noise ratios
are suggested to use; while inferring a PAN of only positive associations,
posterior probability odds or posterior probabilities are preferred.
This function will return a numeric adjacency matrix of edge weights.
Xin Wang xw264@cam.ac.uk
Xin Wang, Mauro Castro, Klaas W. Mulder and Florian Markowetz, Posterior association networks and enriched functional gene modules inferred from rich phenotypic perturbation screens, in preparation.