View source: R/calculate_synergy_score.R
CalculateSynergy | R Documentation |
CalculateSynergy
is the main function for calculating synergy scores
based on model(ZIP, Bliss, Loewe, and HSA) from one dose-response matrix.
CalculateSynergy( data, method = c("ZIP", "HSA", "Bliss", "Loewe"), Emin = NA, Emax = NA, adjusted = TRUE, correct_baseline = "non", iteration = 10, seed = 123 )
data |
A list object generated by function |
method |
A vector of characters. It is used to specify the reference models used to calculate the synergy scores. Choices are "ZIP", "Bliss", "HSA" and "Loewe". Default setting is to calculate all the available models. |
Emin |
The expected minimum response value in the 4 parameter
log-logistic model. It is used while calling |
Emax |
The expected maximum response value in the 4 parameter
log-logistic model. It is used while calling |
adjusted |
A logical value. If it is |
correct_baseline |
A character value. It indicates the method used for baseline correction. Available values are:
|
iteration |
An integer value. It indicates the number of iterations for bootstrap on data with replicates. |
seed |
An integer or NULL. It is used to set the random seed in synergy scores calculation on data with replicates. |
This function will add 1 or 2 elements into inputted data
list:
scores A data frame. It contains synergy scores,
reference effects and fitted response values (only for "ZIP" model)
calculated by selected method
. If there are replicates in the
block, the mean values across all iterations for all the metrics
mentioned above will be output.
scores_statistics A data frame. It will be output if there is block have replicated response values. It contains the the statistics (including mean, standard deviation, standard error of mean and 95 and fitted response values (only for "ZIP" model) across results from iterations.
This function also add mean of synergy scores across whole combination
matrix to the data$drug_pair
table.
Shuyu Zheng shuyu.zheng@helsinki.fi
Jing Tang jing.tang@helsinki.fi
data("mathews_screening_data") data <- ReshapeData(mathews_screening_data) scores <- CalculateSynergy(data)
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