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Adding plotDrugAUCViolinPlot() function; adding drugScreening dataset; update output of selectOrgForOneDrug() function
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‎DESCRIPTION

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@@ -22,6 +22,7 @@ Depends: R (>= 4.0),
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stats,
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utils
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Imports: S4Vectors,
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ggplot2,
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methods
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Suggests: testthat,
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knitr,

‎NAMESPACE

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# Generated by roxygen2: do not edit by hand
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S3method(is,DrugAUCQuantile)
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export(plotDrugAUCDistribution)
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export(plotDrugAUCDensityCurve)
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export(plotDrugAUCViolinPlot)
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export(selectOrgForOneDrug)
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importFrom(S4Vectors,isSingleNumber)
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importFrom(ggplot2,.data)
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importFrom(ggplot2,aes)
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importFrom(ggplot2,element_text)
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importFrom(ggplot2,geom_hline)
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importFrom(ggplot2,geom_point)
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importFrom(ggplot2,geom_violin)
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importFrom(ggplot2,ggplot)
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importFrom(ggplot2,position_jitter)
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importFrom(ggplot2,scale_colour_manual)
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importFrom(ggplot2,theme)
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importFrom(ggplot2,theme_minimal)
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importFrom(ggplot2,xlab)
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importFrom(ggplot2,ylab)
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importFrom(ggplot2,ylim)
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importFrom(methods,is)
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importFrom(stats,quantile)

‎R/OrganoidsToolBox.R

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#' Simple demo drug screening for one drug (Methotrexate). The results have
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#' been generated for demonstration purpose.
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#' been generated for demonstration purpose. There is only one study in the
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#' dataset. There is also only one type 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.
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#'
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#' @name simpleDrugScreening
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#'
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#'
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#'
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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 drugScreening
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#'
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#' @docType data
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#'
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#' @aliases drugScreening
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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{plate} { a \code{character} string representing the plate
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#' identifier. }
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#' \item \code{passage_number} { a \code{character} string representing the
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#' passage number of the organoid. }
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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{z_prime} { a \code{numeric} representing the assay quality. }
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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{dosage_concentration_a} { a \code{numeric}
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#' representing the dosage of
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#' the first drug used for the drug screen. This column should always have a
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#' value as there is at least one drug used in a drug screening.}
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#' \item \code{dosage_concentration_b} { a \code{numeric}
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#' representing the dosage of the second drug used for the drug screen.
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#' When no second drug has been used, the value is \code{0}.}
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#' \item \code{dosage_concentration_c} { a \code{numeric}
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#' representing the dosage of the third drug used for the drug screen.
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#' When no third drug has been used, the value is \code{0}. }
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#' \item \code{dosage_concentration_background} { a \code{numeric}
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#' representing the dosage of the background drug used for the drug screen.
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#' When no background drug has been used, the value is \code{0}. }
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#' \item \code{percent_viability} { a \code{numeric}
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#' representing the percentage of viability of the organoids under the
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#' specific screening conditions. }
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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{selectOrgForOneDrug}} { 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(drugScreening)
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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 1 drug
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#' data(drugScreening)
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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 <- selectOrgForOneDrug(drugScreening=drugScreening,
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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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#' results$extreme
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#'
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#'
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NULL

‎R/drugScreening-internal.R

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#'
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#' @examples
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#'
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#' ## Path to the demo pedigree file is located in this package
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#' data.dir <- system.file("extdata", package="RAIDS")
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#' ## Load drug screen dataset for 1 drug
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#' data(simpleDrugScreening)
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#'
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#' ## TODO
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#' ## Calculate the extreme organoids for the methotrexate drug screening
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#' ## using a quantile of 1/4
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#' results <- OrganoidsToolBox:::findOneDrugQuantile(
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#' drugData=simpleDrugScreening,
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#' drugName="Methotrexate", doseType="Averaged", quantile=1/4)
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#'
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#' ## The classification of the organoids is in the 'extreme' entry
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#' results$extreme
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#'
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#' @author Pascal Belleau and Astrid Deschênes
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#' @author Pascal Belleau, Astrid Deschênes
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#' @importFrom stats quantile
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#' @encoding UTF-8
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#' @keywords internal
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results[["quantile"]] <- list()
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## Calculate upper and lower quantile
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results[["quantile"]][["value"]] <- quantile
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results[["quantile"]][["lower"]] <-
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unname(quantile(orgDR.avr.u$relative_auc, quantile))
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results[["quantile"]][["upper"]] <-
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## Select sensitive organoids
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extreme <- orgDR.avr.u[which(orgDR.avr.u$relative_auc <=
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results[["quantile"]][["lower"]]),]
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extreme$GROUP <- rep("SENSITIVE", nrow(extreme))
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extreme$group <- rep("SENSITIVE", nrow(extreme))
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## Select resistant organoids
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extreme2 <- orgDR.avr.u[which(orgDR.avr.u$relative_auc >=
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results[["quantile"]][["upper"]]),]
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extreme2$GROUP <- rep("RESISTANT", nrow(extreme2))
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extreme2$group <- rep("RESISTANT", nrow(extreme2))
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## Select resistant organoids
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extreme3 <- orgDR.avr.u[which(!orgDR.avr.u$organoid_id %in%
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c(extreme$organoid_id, extreme2$organoid_id)),]
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extreme3$group <- rep("AVERAGE", nrow(extreme3))
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final <- rbind(extreme, extreme2)
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final <- final[, c("organoid_id", "relative_auc", "GROUP")]
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final <- rbind(extreme, extreme2, extreme3)
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final <- final[, c("organoid_id", "relative_auc", "group")]
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results[["extreme"]] <- final[order(final$relative_auc, decreasing=FALSE),]
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rownames(results[["extreme"]]) <- NULL
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‎R/drugScreening.R

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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(simpleDrugScreening)
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#' data(drugScreening)
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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 <- selectOrgForOneDrug(drugScreening=simpleDrugScreening,
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#' results <- selectOrgForOneDrug(drugScreening=drugScreening,
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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 classification of the organoids is in the 'extreme' entry
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#' results$extreme
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#'
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#' @author Astrid Deschênes, Pascal Belleau
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#' @importFrom S4Vectors isSingleNumber
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#' @encoding UTF-8
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selectedDrugData <- selectedDrugData[
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which(tolower(selectedDrugData$screen_type) %in% tolower(screenType)), ]
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results <- findOneDrugQuantile(drugData=selectedDrugData, drugName=drugName,
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doseType="Averaged", quantile=quantile)
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results <- findOneDrugQuantile(drugData=selectedDrugData,
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drugName=drugName, doseType="Averaged",
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quantile=quantile)
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# Return a list marked as an DrugAUCQuantile class
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class(results) <- "DrugAUCQuantile"
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#'
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#' @description The function TODO
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#'
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#' @param drugQuantile TODO
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#' @param drugQuantile an object of class "\code{DrugAUCQuantile}" which
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#' contains the
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#' sensitive and resistant organoids for a specific drug.
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#'
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#' @return TODO
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#'
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#' @importFrom S4Vectors isSingleNumber
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#' @encoding UTF-8
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#' @export
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plotDrugAUCDistribution <- function(drugQuantile) {
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plotDrugAUCDensityCurve <- function(drugQuantile) {
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## Validate that the drugQuantile parameter is a DrugAUCQuantile object
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if (!is.DrugAUCQuantile(drugQuantile)) {
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stop("\'drugQuantile\' must be a DrugAUCQuantile object.")
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}
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}
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#' @title TODO
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#'
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#' @description The function TODO
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#'
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#' @param drugQuantile an object of class "\code{DrugAUCQuantile}" which
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#' contains the
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#' sensitive and resistant organoids for a specific drug.
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#'
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#' @param min a single \code{numeric} representing the minimum value of the
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#' y-axis. Default: \code{0}.
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#'
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#' @param max a single \code{numeric} representing the maximum value of the
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#' y-axis. Default: \code{100}.
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#'
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#' @param trim a \code{logical} indicating if the tails of the violins
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#' are trimmed to the range of the data. Default: \code{FALSE}.
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#'
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#' @return a \code{ggplot} object for a violin plot built with the specified
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#' data.
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#'
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#' @examples
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#'
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#' ## TODO
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#' drugName <- "Methotrexate"
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#'
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#' @author Astrid Deschênes, Pascal Belleau
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#' @importFrom ggplot2 ggplot geom_violin ylim ylab theme_minimal aes .data
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#' position_jitter geom_point xlab geom_hline scale_colour_manual theme
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#' element_text
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#' @encoding UTF-8
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#' @export
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plotDrugAUCViolinPlot <- function(drugQuantile, min=0, max=100, trim=FALSE) {
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## Validate that the drugQuantile parameter is a DrugAUCQuantile object
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if (!is.DrugAUCQuantile(drugQuantile)) {
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stop("\'drugQuantile\' must be a DrugAUCQuantile object.")
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}
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aucResults <- drugQuantile$extreme
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aucResults$drug <- drugQuantile$dataset$drug_a
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colorsR <- c("RESISTANT"="red2", "AVERAGE"="darkgray",
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"SENSITIVE"="blue3")
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p <- ggplot(data=aucResults, aes(x=.data$drug, y=.data$relative_auc)) +
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geom_violin(size=1, colour="gray", trim=trim) +
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geom_point(aes(colour = .data$Group), size=3,
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position = position_jitter(seed = 1, width = 0.15)) +
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scale_colour_manual(name="Group", values=colorsR) +
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geom_hline(yintercept=drugQuantile$quantile$lower, linetype="dashed",
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color = "blue3", size=0.9) +
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geom_hline(yintercept=drugQuantile$quantile$upper, linetype="dashed",
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color = "red2", size=0.9) +
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ylab("Relative AUC") + ylim(c(0, 100)) + xlab("") +
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theme_minimal() +
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theme(axis.title=element_text(size=13, face="bold"),
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axis.text.x=element_text(size=13, face="bold"),
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legend.text=element_text(size=12),
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legend.title = element_text(size=13, face="bold"))
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return(p)
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}

‎data/drugScreening.RData

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