Takes the sensitivity data from a PharmacoSet, and summarises them into a drug vs cell line table
Source:R/methods-summarizeSensitivityProfiles.R
summarizeSensitivityProfiles-PharmacoSet-method.Rd
This function creates a table with cell lines as rows and drugs as columns, summarising the drug senstitivity data of a PharmacoSet into drug-cell line pairs
Usage
# S4 method for PharmacoSet
summarizeSensitivityProfiles(
object,
sensitivity.measure = "auc_recomputed",
cell.lines,
profiles_assay = "profiles",
treatment_col = "treatmentid",
sample_col = "sampleid",
drugs,
summary.stat = c("mean", "median", "first", "last", "max", "min"),
fill.missing = TRUE,
verbose = TRUE
)
Arguments
- object
PharmacoSet The PharmacoSet from which to extract the data
- sensitivity.measure
character The sensitivity measure to use. Use the sensitivityMeasures function to find out what measures are available for each object.
- cell.lines
character The cell lines to be summarized. If any cell lines have no data, they will be filled with missing values.
- profiles_assay
character The name of the assay in the PharmacoSet object that contains the sensitivity profiles.
- treatment_col
character The name of the column in the profiles assay that contains the treatment IDs.
- sample_col
character The name of the column in the profiles assay that contains the sample IDs.
- drugs
character The drugs to be summarized. If any drugs have no data, they will be filled with missing values.
- summary.stat
character The summary method to use if there are repeated cell line-drug experiments. Choices are "mean", "median", "first", "last", "max", or "min".
- fill.missing
Should the missing cell lines not in the molecular data object be filled in with missing values?
- verbose
Should the function print progress messages?
Value
matrix A matrix with cell lines going down the rows, drugs across the columns, with the selected sensitivity statistic for each pair.
Examples
data(GDSCsmall)
GDSCauc <- summarizeSensitivityProfiles(GDSCsmall,
sensitivity.measure='auc_published')