findResiduals {bnem} | R Documentation |
calculates residuals (data and optimized network do not match) and visualizes them
findResiduals( bString, CNOlist, model, fc = NULL, expression = NULL, egenes = NULL, parameters = list(cutOffs = c(0, 1, 0), scoring = c(0.1, 0.2, 0.9)), method = "s", sizeFac = 10^-10, main = "residuals for decoupled vertices", sub = paste0("green residuals are added effects (left positive,", " right negative) and red residuals are deleted ", "effects"), cut = TRUE, parallel = NULL, verbose = TRUE, ... )
bString |
Binary vector denoting the network given a model |
CNOlist |
CNOlist object (see package CellNOptR), if available. |
model |
Model object including the search space, if available. See CellNOptR::preprocessing. |
fc |
m x l matrix of foldchanges of gene expression values or equivalent input (normalized pvalues, logodds, ...) for m E-genes and l contrasts. If left NULL, the gene expression data is used to calculate naive foldchanges. |
expression |
Optional normalized m x l matrix of gene expression data for m E-genes and l experiments. |
egenes |
list object; each list entry is named after an S-gene and contains the names of egenes which are potential children |
parameters |
parameters for discrete case (not recommended); has to be a list with entries cutOffs and scoring: cutOffs = c(a,b,c) with a (cutoff for real zeros), b (cutoff for real effects), c = -1 for normal scoring, c between 0 and 1 for keeping only relevant between -1 and 0 for keeping only a specific quantile of E-genes, and c > 1 for keeping the top c E-genes; scoring = c(a,b,c) with a (weight for real effects), c (weight for real zeros), b (multiplicator for effects/zeros between a and c); |
method |
Scoring method can be "cosine", a correlation, or a distance measure. See ?cor and ?dist for details. |
sizeFac |
Size factor penelizing the hyper-graph size. |
main |
Main title of the figure. |
sub |
Subtitle of the figure. |
cut |
If TRUE does not visualize experiments/S-genes which do not have any residuals. |
parallel |
Parallelize the search. An integer value specifies the number of threads on the local machine or a list object as in list(c(1,2,3), c("machine1", "machine2", "machine3")) specifies the threads distributed on different machines (local or others). |
verbose |
TRUE for verbose output |
... |
additional parameters for epiNEM::HeatmapOP |
numeric matrices indicating experiments and/or genes, where the network and the data disagree
Martin Pirkl
sifMatrix <- rbind(c("A", 1, "B"), c("A", 1, "C"), c("B", 1, "D"), c("C", 1, "D")) temp.file <- tempfile(pattern="interaction",fileext=".sif") write.table(sifMatrix, file = temp.file, sep = "\t", row.names = FALSE, col.names = FALSE, quote = FALSE) PKN <- CellNOptR::readSIF(temp.file) CNOlist <- dummyCNOlist("A", c("B","C","D"), maxStim = 1, maxInhibit = 2, signal = c("A", "B","C","D")) model <- CellNOptR::preprocessing(CNOlist, PKN, maxInputsPerGate = 100) expression <- matrix(rnorm(nrow(slot(CNOlist, "cues"))*10), 10, nrow(slot(CNOlist, "cues"))) fc <- computeFc(CNOlist, expression) initBstring <- rep(0, length(model$reacID)) res <- bnem(search = "greedy", CNOlist = CNOlist, fc = fc, model = model, parallel = NULL, initBstring = initBstring, draw = FALSE, verbose = FALSE, maxSteps = Inf) rownames(fc) <- seq_len(nrow(fc)) ## val <- validateGraph(CNOlist = CNOlist, fc = fc, model = model, ## bString = res$bString, Egenes = 10, Sgene = 4) residuals <- findResiduals(res$bString, CNOlist, model, fc = fc)