Using one of the network building algorithms, cluster initial network into individual protein complexes.
Usage
X.postprocess(
data = NULL,
mode = "trim",
scores.col = NA,
weighted = FALSE,
zcut = 2,
init.stats = FALSE,
final.stats = FALSE,
standard.set = NULL,
labels.col = NA
)Arguments
- data
Data frame with pair-wise interactions (columns 'protein1' and 'protein2') and a column with probabilities from ML model.
- mode
Character string: 'trim' for trimming of not-well-connected proteins and 'split' for separating of two loosely connected subunits. Default is 'trim'.
- scores.col
Character string: Name of the columns with prediction values.
- zcut
Numeric: Sub-units with z-score above this value will be removed. Default is 2.
- init.stats
Logical: Should the initial network stats be calculated? Default is FALSE.
- final.stats
Logical: Should the final network stats be calculated? Default is FALSE.
- standard.set
Data frame with columns protein1, protein2 and another column with labels.
- labels.col
Character string: Name of the columns with labels.
- weight
Logical: Should the prediction values be taken into account for the postprocessing? Default is FALSE
Value
A list with three elements: $data with columns 'protein1', 'protein2' and score contains all data for plotting or further processing of the network, 'stats_initial' contains statistics of the network before clustering. and 'stats_final' contains statistics of the network after clustering.
Examples
network.post.split <- X.postprocess(data=network.refined$data, mode="split", scores.col="score", final.stats=TRUE,
standard.set=GS,labels="complex", weighted=FALSE)
#> Error: object 'network.refined' not found
network.post.trim <- X.postprocess(data=network.post.split$data, mode="trim", scores.col="score", final.stats=TRUE,
standard.set=GS,labels="complex", weighted=TRUE)
#> Error: object 'network.post.split' not found