library(CellNOptR)
library(dplyr)
data_file <- system.file("extdata/datasets", "MD-TCellPCB2007.csv",
                         package = "artemis")
model_file <- system.file("extdata/models", "PKN-TCellPCB2007.sif", 
            package = "artemis")
tcell_data <- CNOlist(data_file)
tcell_model <- readSIF(model_file)
preprocessing(tcell_data, tcell_model, expansion = FALSE) %>%
  plotModel(tcell_data)

The following is a model that blends a T-cell signaling prior knowledge network and a single cell AML study. The data is not real, but engineered such that it shows the overlap between the model and the data set. Not the pi3K -- Akt edge was added to the original sif representaion of the model so akt could be included.

data_file <- system.file("extdata/datasets", "TCell_fake.csv",
                         package = "artemis")
model_file <- system.file("extdata/models", "TCellConstructed.sif", 
            package = "artemis")
tcell_data <- CNOlist(data_file)
tcell_model <- readSIF(model_file)
preprocessing(tcell_data, tcell_model, expansion = FALSE) %>%
  plotModel(tcell_data)

Now working with the hepatocellular carcinoma cells discussed in Saez-Rodriguez, Lauffenburger, Klamt and Sorger et al's 2009 paper on logic modeling of signaling networks.

data_file <- system.file("extdata/datasets", "MD-ExtLiverPCB1.csv",
                         package = "artemis")
model_file <- system.file("extdata/models", "PKN-ExtLiverPCB.sif", 
            package = "artemis")
tcell_data <- CNOlist(data_file)
tcell_model <- readSIF(model_file)
preprocessing(tcell_data, tcell_model, expansion = FALSE) %>%
  plotModel(tcell_data)


robertness/artemis documentation built on May 27, 2019, 10:32 a.m.