predictPPI: Prediction of the PPI
In Path2PPI: Prediction of pathway-related protein-protein interaction networks

Description Usage Arguments Details Value Author(s) See Also Examples

Major method of the Path2PPI class to predict the final PPI in the target species using the information available from the stored reference species. Different values for the arguments of this method can lead to different PPI networks, differing in the degree of reliability and strictness.

predictPPI(path2ppi, mode="both", h.thresh=1e-05, 
           h.range=c(1e-100, 1e-20), i.thresh=0.7, 
           consider.complexes=FALSE, max.complex.size=5,
           decline.self.interaction.ref=FALSE,
           decline.self.interaction.tar=TRUE,
           verbose=TRUE)

`path2ppi`	An object of the class `Path2PPI`.
`mode`	Which interaction from the reference species should be taken into account. "both": both interactors of an interaction has to be in the initial protein list previously inserted by the user (recommended if it is a large network or many proteins were initially defined, respectively). "one": only one of the interactors of each reference interaction has to be in the initial protein list (may lead to very large networks).
`h.thresh`	E-value cutoff at which each homologous relationship definitely will be declined (see also `h.range` argument).
`h.range`	Numeric vector consisting of two values. The first value indicates the lower border (smallest E-value). Each E-value which is equal or less than this border is scored with 1 (best). The second value indicates the upper border (biggest E-value). Each E-value which is equal or greater than this border is scored with 0 (worst).
`i.thresh`	Numeric. Threshold for accepted interactions. If the computed prediction score for an interaction is less than `i.thresh` it will be declined.
`consider.complexes`	Logical. If `TRUE` then interactions are also considered which actually indicate an association of the current protein to one bigger protein complex. This may lead to very large networks if `mode="one"` since all other proteins of this complex are considered as well, i.e., each protein in such complexes are considered to interact with each other protein of this complex. If `mode="both"` then each protein of an complex has to be in the initial protein list to consider each interaction (see details).
`max.complex.size`	Numeric. Is only considered if `consider.complexes=TRUE`. The maximum size of complexes to be considered.
`decline.self.interaction.ref`	Logical. If `TRUE` then all self interactions from reference species are declined.
`decline.self.interaction.tar`	Logical. If `TRUE` then all predicted self interactions in target species are declined.
`verbose`	Logical. `FALSE` hides messages in the output.

Difference of h.thresh and h.range: If only one protein in the target species was found to be homologous to a current reference species protein and this homology was rated with an E-value which is equal or smaller than h.thresh it is scored with 1 (even if the E-value is larger than the upper border of h.range). See package vignette for more details.

Use the complex arguments with care, since each complex may lead to a vast amount of interactions, i.e., each protein is considered to interact with each other of this complex; e.g. if there are 10 proteins involved in one complex, this would lead to 10 over 2 = 45 interactions.

An object of the class Path2PPI with predicted PPI.

Oliver Philipp MolBI-software@bioinformatik.uni-frankfurt.de

plot.Path2PPI, homologyScore

data(ai) #Load test data set

ppi <- Path2PPI("Autophagy induction", "Podospora anserina", "5145")
ppi <- addReference(ppi, "Homo sapiens", "9606", human.ai.proteins, 
                    human.ai.irefindex, pa2human.ai.homologs)
ppi <- addReference(ppi, "Saccharomyces cerevisiae (S288c)", "559292", 
                    yeast.ai.proteins, yeast.ai.irefindex, 
                    pa2yeast.ai.homologs)

#Using the default settings leads to 8 predicted interactions in the 
#target species
ppi <- predictPPI(ppi)

#Consider complexes where each complex is allowed to be up to 10 proteins 
#large. For this smaller pathway only one more interaction was predicted when 
#considering larger complexes.
ppi <- predictPPI(ppi,consider.complexes=TRUE,max.complex.size=10)

#We can be less strict and decrease h.range what obviously increases the 
#number of predicted interactions to 13
ppi <- predictPPI(ppi,h.range=c(1e-60,1e-20))

Loading required package: igraph

Attaching package: 'igraph'

The following objects are masked from 'package:stats':

    decompose, spectrum

The following object is masked from 'package:base':

    union

Search for all relevant interactions:
0%--25%--50%--75%--100%
Remove irrelevant homologs.
Search for all relevant interactions:
0%--25%--50%--75%--100%
Remove irrelevant homologs.
Begin with Homo sapiens
6 interactions processed. These lead to 0 interactions in target species.
-------------------------------
Begin with Saccharomyces cerevisiae (S288c)
15 interactions processed. These lead to 8 interactions in target species.
-------------------------------
Combine results to one single PPI.
A total of 8 putative interactions were predicted in target species.
Begin with Homo sapiens
9 interactions processed. These lead to 0 interactions in target species.
-------------------------------
Begin with Saccharomyces cerevisiae (S288c)
24 interactions processed. These lead to 17 interactions in target species.
-------------------------------
Combine results to one single PPI.
A total of 9 putative interactions were predicted in target species.
Begin with Homo sapiens
6 interactions processed. These lead to 5 interactions in target species.
-------------------------------
Begin with Saccharomyces cerevisiae (S288c)
15 interactions processed. These lead to 22 interactions in target species.
-------------------------------
Combine results to one single PPI.
A total of 13 putative interactions were predicted in target species.