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Adding new data examples
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‎R/OrganoidsToolBox.R

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@@ -210,6 +210,90 @@ NULL
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NULL
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#' Simple demo drug screening for one drug (Methotrexate). The results have
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#' been generated for demonstration purpose. There is two studies present in
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#' the dataset. There is also only two types of screening in the dataset. Some
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#' entries have a value for a second drug. There is not entry for a third
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#' drug. There is no background drug. At last, there is two types of dosage.
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#'
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#' @name drugScreeningMethoSet
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#'
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#' @docType data
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#'
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#' @aliases drugScreeningMethoSet
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#'
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#' @format a \code{data.frame} with the following columns:
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#' \itemize{
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#' \item \code{organoid_id} { a \code{character} string representing the
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#' organoid identifier. }
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#' \item \code{timestamp} { a \code{character} string representing the date
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#' when the screening was done. }
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#' \item \code{study} { a \code{character} string representing the study. }
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#' \item \code{screen_type} { a \code{character} string representing the
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#' screen type. }
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#' \item \code{drug_a} { a \code{character} string representing the name of
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#' the first drug used for the drug screen. There is at least one drug used
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#' in a drug screening.}
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#' \item \code{drug_b} { a \code{character} string representing the name of
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#' the second drug used for the drug screen. When no second drug has been
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#' used, the value is \code{'N/A'}. }
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#' \item \code{drug_c} { a \code{character} string representing the name of
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#' the third drug used for the drug screen. When no third drug has been
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#' used, the value is \code{'N/A'}. }
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#' \item \code{drug_background} { a \code{character} string representing the
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#' name of
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#' the drug used as background for the drug screen. When no drug has been used
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#' as background, the value is \code{'N/A'}. }
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#' \item \code{dosage_type} { a \code{character} string representing the type
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#' of dosage. }
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#' \item \code{relative_auc} { a \code{numeric}
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#' representing the relative AUC (area under the curve) for the specified
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#' organoids under specific conditions. The AUC is calculated using the
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#' percentage of viability under different drug concentrations. So, the same
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#' relative AUC is repeated on multiple lines.}
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#' }
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#'
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#' @seealso
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#' \itemize{
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#' \item \code{\link{getClassOneDrug}} { for selecting the organoids
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#' with sensitive and resistant behavior for a
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#' specific drug screening.}
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#' }
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#'
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#' @usage data(drugScreeningMethoSet)
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#'
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#' @keywords datasets
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#'
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#' @examples
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#'
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#' ## Load drug screen dataset and patient information for methotrexate
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#' data(drugScreeningMethoSet)
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#' data(patientInfoMethoSet)
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#'
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#' ## Retain unreplicated samples
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#' cleanData <- selectNoReplicateOrganoids(drugScreening=drugScreeningMethoSet,
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#' patientInfo=patientInfoMethoSet)
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#'
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#' ## Calculate the extreme organoids for the methotrexate drug screening
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#' ## using a quantile of 1/3
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#' results <- getClassOneDrug(drugScreening=cleanData,
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#' drugName="Methotrexate", study="MEGA-TEST", screenType="TEST-01",
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#' doseType="Averaged", quantile=1/3)
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#'
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#' ## The information of the extreme organoids is found it the 'extreme' entry
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#' head(results$extreme)
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#'
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#' ## Fisher test on ancestry
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#' fisherT <- fisherCategoricalVariable(drugQuantile=results,
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#' category="ancestry")
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#'
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#' fisherT
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#'
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NULL
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#' Simple demo patient information dataset. The information is related to the
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#' organoids present in the 'drugScreening' dataset.
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#'
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#' \item \code{\link{selectNoReplicateOrganoids}} { for selecting
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#' the unrelated samples (only one sample per patient) from a drug screening
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#' dataset.}
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#' \item \code{\link{fisherCategoricalVariable}} { for running Fisher tests
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#' in the sensitive and resistant groups using a categorical value
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#' from a drug screening dataset.}
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#' }
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#'
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#' @usage data(drugScreening)
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#' @usage data(patientInfo)
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#'
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#' @keywords datasets
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#'
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#'
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#'
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NULL
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#' Simple demo patient information dataset. The information is related to the
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#' organoids present in the 'drugScreening' dataset.
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#'
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#' @name patientInfoMethoSet
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#'
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#' @docType data
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#'
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#' @aliases patientInfoMethoSet
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#'
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#' @format a \code{data.frame} with the following columns:
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#' \itemize{
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#' \item \code{organoid_id} { a \code{character} string representing the
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#' organoid identifier. }
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#' \item \code{patient_id} { a \code{character} string representing the patient
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#' identifier. }
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#' \item \code{ancestry} { a \code{character} string representing the patient
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#' genetic ancestry. }
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#' \item \code{BMI} { a \code{character} string representing the patient
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#' BMI class. }
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#' }
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#'
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#' @seealso
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#' \itemize{
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#' \item \code{\link{getClassOneDrug}} { for selecting the samples
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#' with sensitive and resistant behavior for a
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#' specific drug screening dataset.}
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#' \item \code{\link{selectNoReplicateOrganoids}} { for selecting
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#' the unrelated samples (only one sample per patient) from a drug screening
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#' dataset.}
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#' \item \code{\link{fisherCategoricalVariable}} { for running Fisher tests
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#' in the sensitive and resistant groups using a categorical value
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#' from a drug screening dataset.}
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#' }
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#'
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#' @usage data(patientInfoMethoSet)
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#'
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#' @keywords datasets
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#'
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#' @examples
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#'
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#' ## Load drug screen dataset for methotrexate dataset
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#' data(drugScreening)
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#'
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#' ## Load patient information dataset for methotrexate dataset
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#' data(patientInfoMethoSet)
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#'
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#' ## Retain unreplicated samples
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#' cleanData <- selectNoReplicateOrganoids(drugScreening=drugScreeningMethoSet,
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#' patientInfo=patientInfoMethoSet)
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#'
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#' ## Calculate the extreme organoids for the methotrexate drug screening
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#' ## using a quantile of 1/3
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#' results <- getClassOneDrug(drugScreening=cleanData,
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#' drugName="Methotrexate", study="MEGA-TEST", screenType="TEST-01",
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#' doseType="Averaged", quantile=1/4)
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#'
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#' ## The information of the extreme organoids is found it the 'extreme' entry
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#' head(results$extreme)
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#'
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#' ## Fisher test on BMI
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#' fisherT <- fisherCategoricalVariable(drugQuantile=results, category="BMI")
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#'
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#' fisherT
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#'
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#'
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NULL

‎R/enrichment.R

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#'
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#' @examples
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#'
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#' ## Load drug screen dataset for 1 drug
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#' data(drugScreening)
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#' ## Load drug screen dataset and patient information for methotrexate
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#' data(drugScreeningMethoSet)
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#' data(patientInfoMethoSet)
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#'
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#' ## Retain unreplicated samples
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#' cleanData <- selectNoReplicateOrganoids(drugScreening=drugScreeningMethoSet,
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#' patientInfo=patientInfoMethoSet)
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#'
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#' ## Calculate the extreme organoids for the methotrexate drug screening
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#' ## using a quantile of 1/3
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#' results <- getClassOneDrug(drugScreening=drugScreening,
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#' results <- getClassOneDrug(drugScreening=cleanData,
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#' drugName="Methotrexate", study="MEGA-TEST", screenType="TEST-01",
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#' doseType="Averaged", quantile=1/3)
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#'
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#' ## TODO
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#' results$extreme
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#' ## Fisher test on ancestry
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#' fisherT <- fisherCategoricalVariable(drugQuantile=results,
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#' category="ancestry")
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#'
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#' @author Astrid Deschênes, Pascal Belleau
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#' @importFrom stats fisher.test
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}
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## The drug must be present in the drug dataset
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if (!(category %in% colnames(drugQuantile$extreme))) {
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if (!(category %in% colnames(drugQuantile$extreme) ||
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category %in% colnames(drugQuantile$dataset))) {
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stop("The category \'", category, "\' must be one of the columns in ",
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"the \'DrugAUCQuantile\' dataset.")
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}
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results <- drugQuantile$extreme
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if (!(category %in% colnames(drugQuantile$extreme))) {
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results <- merge(results, drugQuantile$dataset[,
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c("organoid_id", category)],
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by="organoid_id", all.x=TRUE, all.y=FALSE)
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}
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sensitive <- results[results$group == "SENSITIVE",]
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resistant <- results[results$group == "RESISTANT",]
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result <- list()
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result[["Fisher"]] <- fisherResult
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result[["table"]] <- allTable
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result[["category"]] <- category
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return(result)
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}

‎data/drugScreeningMethoSet.RData

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‎data/patientInfoMethoSet.RData

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‎man/drugScreeningMethoSet.Rd

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‎man/fisherCategoricalVariable.Rd

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‎man/patientInfo.Rd

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