sbpiper (version 1.9.0)

sbpiper_ps1: Main R function for SBpipe pipeline: parameter_scan1().

Description

Main R function for SBpipe pipeline: parameter_scan1().

Usage

sbpiper_ps1(model, inhibition_only, inputdir, outputdir, run, percent_levels,
  min_level, max_level, levels_number, homogeneous_lines, xaxis_label,
  yaxis_label)

Arguments

model

the model name

inhibition_only

true if the the variable amount can only decrease

inputdir

the input directory containing the simulated data

outputdir

the output directory that will contain the simulated plots

run

the simulation number

percent_levels

true if scanning levels are in percent

min_level

the minimum level

max_level

the maximum level

levels_number

the number of levels

homogeneous_lines

true if lines should be plotted homogeneously

xaxis_label

the label for the x axis (e.g. Time (min))

yaxis_label

the label for the y axis (e.g. Level (a.u.))

Examples

# NOT RUN {
data(insulin_receptor_ps1_l0)
data(insulin_receptor_ps1_l1)
data(insulin_receptor_ps1_l3)
data(insulin_receptor_ps1_l4)
data(insulin_receptor_ps1_l6)
data(insulin_receptor_ps1_l8)
data(insulin_receptor_ps1_l9)
data(insulin_receptor_ps1_l11)
data(insulin_receptor_ps1_l13)
data(insulin_receptor_ps1_l14)
data(insulin_receptor_ps1_l16)
dir.create(file.path("ps1_datasets"))
write.table(insulin_receptor_ps1_l0, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_0.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l1, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_1.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l3, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_3.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l4, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_4.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l6, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_6.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l8, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_8.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l9, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_9.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l11, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_11.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l13, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_13.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l14, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_14.csv"), 
            row.names=FALSE)
write.table(insulin_receptor_ps1_l16, 
            file=file.path("ps1_datasets",
                           "insulin_receptor_scan_IR_beta__rep_1__level_16.csv"), 
            row.names=FALSE)
sbpiper_ps1(
       model="insulin_receptor_scan_IR_beta", 
       inhibition_only=FALSE,
       inputdir="ps1_datasets", 
       outputdir="ps1_plots",
       run=1,
       percent_levels=TRUE, 
       min_level=0, 
       max_level=250, 
       levels_number=10,
       homogeneous_lines=FALSE,
       xaxis_label="Time [m]", 
       yaxis_label="Level [a.u.]")
# }