Synergy

library(synergyfinder)

res <- ReshapeData(

          data = dat,

        data_type = "inhibition", #viability

       impute = TRUE,

      impute_method = NULL,

        noise = TRUE,

       seed = 1)

res <- CalculateSynergy(

     data = res,

     method = c("ZIP", "HSA", "Bliss", "Loewe"),

     Emin = NA,

     Emax = NA,

     correct_baseline = "non")

res <- CalculateSensitivity(

     data = res,

     correct_baseline = "non"

 )

Plot2DrugContour(

    data = res,

    plot_block = 1,

    drugs = c(1, 2),

    plot_value = "response",

    dynamic = FALSE,

    summary_statistic = c("mean", "median"))

Plot2DrugSurface(

data = res,

  plot_block = 1,

  drugs = c(1, 2),

plot_value = "ZIP_synergy", #Bliss

dynamic = FALSE,

summary_statistic = c("mean", "quantile_25", "median", "quantile_75")

)

Plot2DrugSurface(

data = res,

  plot_block = 1,

  drugs = c(1, 2),

plot_value = "response",

dynamic = FALSE,

summary_statistic = c("mean", "quantile_25", "median", "quantile_75")

)

PlotDoseResponse(

data = res,

  block_ids = 1,

drugs = c(1,2),

  save_file = TRUE,

   file_type = "png")

PlotBarometer(

    data = res,

    plot_block = 1,

    plot_concs = c(12, 10), 

    needle_text_offset = 2

))

PlotDoseResponseCurve(

    data = res,

    plot_block = 1,

    drug_index = i,

    plot_new = FALSE,

    record_plot = FALSE

  )

Data format

block_id	drug1	drug2	cell_line_name	conc1	conc2	response	conc_unit
1	BAY	STF	MCF	0	1	91.5	nM
1	BAY	STF	MCF	0	0.5	50	nM
1	BAY	STF	MCF	0	0.25	20	nM
1	BAY	STF	MCF	0	0.125	10	nM
1	BAY	STF	MCF	0	0.063	1.2	nM
1	BAY	STF	MCF	0	0.01	0.6	nM
1	BAY	STF	MCF	0	0	0	nM
1	BAY	STF	MCF	0.05	1	95	nM
1	BAY	STF	MCF	0.05	0.5	60	nM
1	BAY	STF	MCF	0.05	0.25	12	nM
1	BAY	STF	MCF	0.05	0.125	8	nM
1	BAY	STF	MCF	0.05	0.063	6	nM
1	BAY	STF	MCF	0.05	0.01	3	nM
1	BAY	STF	MCF	0.05	0	0	nM