runCARNIVAL
runCARNIVAL(
inputObj = NULL,
measObj = measObj,
netObj = netObj,
weightObj = NULL,
solverPath = NULL,
solver = c("lpSolve", "cplex", "cbc", "gurobi"),
timelimit = 3600,
mipGAP = 0.05,
poolrelGAP = 1e-04,
limitPop = 500,
poolCap = 100,
poolIntensity = 4,
poolReplace = 2,
alphaWeight = 1,
betaWeight = 0.2,
threads = 0,
cleanTmpFiles = TRUE,
keepLPFiles = TRUE,
clonelog = -1,
dir_name = getwd()
)Data frame of the list for target of perturbation - optional or default set to NULL to run invCARNIVAL when inputs are not known.
Data frame of the measurement file (i.e. DoRothEA normalised enrichment scores) - always required.
Data frame of the prior knowledge network - always required.
Data frame of the additional weight (i.e. PROGENy pathway score or measured protein activities) - optional or default set as NULL to run CARNIVAL without weights.
Path to executable cbc/cplex file - default set to NULL, in which case the solver from lpSolve package is used.
Solver to use: lpSolve/cplex/cbc (Default set to lpSolve).
CPLEX/Cbc parameter: Time limit of CPLEX optimisation in seconds (default set to 3600).
CPLEX parameter: the absolute tolerance on the gap between the best integer objective and the objective of the best node remaining. When this difference falls below the value of this parameter, the linear integer optimization is stopped (default set to 0.05)
CPLEX/Cbc parameter: Allowed relative gap of accepted solution comparing within the pool of accepted solution (default: 0.0001)
CPLEX parameter: Allowed number of solutions to be generated (default: 500)
CPLEX parameter: Allowed number of solution to be kept in the pool of solution (default: 100)
CPLEX parameter: Intensity of solution searching (0,1,2,3,4 - default: 4)
CPLEX parameter: Replacement strategy of solutions in the pool (0,1,2 - default: 2 = most diversified solutions)
Objective function: weight for mismatch penalty (default: 1 - will only be applied once measurement file only contains discrete values)
Objective function: weight for node penalty (default: 0.2)
CPLEX/CBC parameter: Number of threads to use default: 0 for maximum number possible threads on system
logic (default-TRUE), specifying if the tmp files made by solvers should be cleaned after run.
logic (default=TRUE), specifying if the LP file should be kept.
determines if CPLEX clones the log files in case of multi-threaded optimization, default: -1, (no cloning)
Specify directory name to store results. by default set to NULL
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.
Run CARNIVAL pipeline using to the user-provided list of inputs or run CARNIVAL built-in examples. The function is from v1.2 of CARNIVAL and is left for backward compatibility.
load(file = system.file("toy_perturbations_ex1.RData",
package="CARNIVAL"))
load(file = system.file("toy_measurements_ex1.RData",
package="CARNIVAL"))
load(file = system.file("toy_network_ex1.RData",
package="CARNIVAL"))
## lpSolve
#res1 = runCARNIVAL(inputObj = toy_perturbations_ex1,
# measObj = toy_measurements_ex1,
# netObj = toy_network_ex1,
# solver = 'lpSolve')
#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 = runCARNIVAL(inputObj = toy_perturbations_ex1,
## measObj = toy_measurements_ex1,
## netObj = toy_network_ex1,
## solver = 'cbc')
##
## res2$weightedSIF ##see @return
## res2$nodesAttributes ## see @return
## res2$sifAll ## see @return
## res2$attributesAll ## see @return
##
## cplex
## res3 = runCARNIVAL(inputObj = toy_perturbations_ex1,
## measObj = toy_measurements_ex1,
## netObj = toy_network_ex1,
## solver = 'cplex')
##
## res3$weightedSIF ##see @return
## res3$nodesAttributes ## see @return
## res3$sifAll ## see @return
## res3$attributesAll ## see @return