runInverseCarnival: 'runInverseCarnival'

In saezlab/CARNIVAL: A CAusal Reasoning tool for Network Identification (from gene expression data) using Integer VALue programming

runInverseCarnival

Description

runInverseCarnival

Usage

runInverseCarnival(
  measurements,
  priorKnowledgeNetwork,
  weights = NULL,
  carnivalOptions = defaultLpSolveCarnivalOptions()
)

Arguments

measurements	vector of the measurements (i.e. DoRothEA/VIPER normalised enrichment scores)
priorKnowledgeNetwork	data frame of the prior knowledge network
weights	(optional) vector of the additional weights: e.g. PROGENy pathway score or measured protein activities.
carnivalOptions	the list of options for the run. See defaultLpSolveCarnivalOptions(), defaultLpSolveCarnivalOptions, defaultCbcCarnivalOptions.

Details

TODO Replace with correct description

Value

The function will return a list of results containing:

1. weightedSIF: A table with 4 columns containing the combined network solutions from CARNIVAL. It contains the Source of the interaction (Node1), Sign of the interaction (Sign), the Target of the interaction (Node2) and the weight of the interaction (Weight) which shows how often an interaction appears across all solutions.

2. nodesAttributes: A table with 6 columns containing information about infered protein activity states and attributes. It contains the Protein IDs (Node); how often this node has taken an activity of 0, 1 and -1 across the solutions (ZeroAct, UpAct, DownAct); the average activities across solutions (AvgAct); and the node attribute (measured, target, inferred).

3. sifAll: A list of separate network solutions.

4. attributesAll: A list of separate inferred node activities in each solution.

5. diagnostics: reports the convergence of optimization and reason of the termination. Only for CPLEX solver.

Author(s)

Enio Gjerga, Olga Ivanova 2020-2021 [e-mail]

Examples

load(file = system.file("toy_measurements_ex1.RData",
                       package="CARNIVAL"))
load(file = system.file("toy_network_ex1.RData",
                       package="CARNIVAL"))

## lpSolve
#res1 = runInverseCarnival(measurements = toy_measurements_ex1,
#                          priorKnowledgeNetwork = toy_network_ex1,
#                          carnivalOptions = defaultLpSolveCarnivalOptions())

#res1$weightedSIF ##see @return
#res1$nodesAttributes ## see @return
#res1$sifAll ## see @return
#res1$attributesAll ## see @return

## Examples for cbc and cplex are commented out because these solvers are not part of R environment
## and need to be installed separately
##
## cbc
## res2 = runInverseCarnival(measurements = toy_measurements_ex1,
##                           priorKnowledgeNetwork = toy_network_ex1,
##                           carnivalOptions = defaultCbcCarnivalOptions())
##
## res2$weightedSIF ##see @return
## res2$nodesAttributes ## see @return
## res2$sifAll ## see @return
## res2$attributesAll ## see @return
##
## cplex
## res3 = runVanillaCarnival(measurements = toy_measurements_ex1,
##                           priorKnowledgeNetwork = toy_network_ex1,
##                           carnivalOptions = defaultCplexCarnivalOptions())
##
## res3$weightedSIF ##see @return
## res3$nodesAttributes ## see @return
## res3$sifAll ## see @return
## res3$attributesAll ## see @return

saezlab/CARNIVAL documentation built on Jan. 17, 2024, 5:10 p.m.