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checkexperiment <- function(id,db="cytotox")
{
    databases <- data.frame(
        responsetype=c("viability","activity","response"),
        testtype=c("celltype","enzyme","organism"),
        exptype=c("plate","plate","experiment"))
    rownames(databases) <- c("cytotox","enzymes","ecotox")

    if (!(db %in% rownames(databases))) stop("Database does not exist")

    library(RODBC) 
    channel <- odbcConnect(db,uid="cytotox",pwd="cytotox",case="tolower")

    responsetype = as.character(databases[db,1])
    testtype = as.character(databases[db,2])
    exptype = as.character(databases[db,3])
        
    expquery <- paste("SELECT experimentator,substance,",
        testtype,",conc,unit,",responsetype,",performed,ok",
        "FROM ",db," WHERE ",exptype,"=", id)

    expdata <- sqlQuery(channel,expquery)

    if (db %in% c("cytotox","enzymes")) {
        controlquery <- paste("SELECT type,response FROM controls 
            WHERE plate=",id)
        controldata <- sqlQuery(channel,controlquery)
    }

    odbcClose(channel)

    if (db %in% c("cytotox","enzymes")) {
        blinds <- subset(controldata,type=="blind")
        controls <- subset(controldata,type=="control")

        numberOfBlinds <- length(blinds$response)
        stdOfBlinds <- sd(blinds$response)
    } else {
        controls <- subset(expdata,conc == 0)

        numberOfBlinds <- NA
        stdOfBlinds <- NA
        
    }


    if (length(expdata$experimentator) < 1) {
        stop("There is no response data for ",exptype," ",
            id," in database ",db,"\n")
    } 
    expdata$experimentator <- factor(expdata$experimentator)
    expdata$type <- factor(expdata[[testtype]])
    expdata$substance <- factor(expdata$substance)
    expdata$unit <- factor(expdata$unit)
    expdata$performed <- factor(expdata$performed)
    expdata$ok <- factor(expdata$ok)
    
    numberOfControls <- length(controls$response)
    
    meanOfBlinds <- mean(blinds$response)
    meanOfControls <- mean(controls$response)
    stdOfControls <- sd(controls$response)
    percentstdOfcontrols <-stdOfControls *100/meanOfControls
    
    cat("Plate ",plate," from database ",db,"\n",
        "\tExperimentator: ",levels(platedata$experimentator),"\n",
        "\tType(s): ",levels(platedata$type),"\n",
        "\tPerformed on : ",levels(platedata$performed),"\n",
        "\tSubstance(s): ",levels(platedata$substance),"\n",
        "\tConcentration unit: ",levels(platedata$unit),"\n",
        "\tOK: ",levels(platedata$ok),"\n",
        "\t\tNumber \tMean \t\tStandard Deviation \t% Standard Deviation \n",
        "\tblind\t",numberOfBlinds,"\t",meanOfBlinds,"\t",stdOfBlinds,"\n",
        "\tcontrol\t",numberOfControls,"\t",meanOfControls,"\t",stdOfControls,"\t\t",percentstdOfcontrols,"\n")
    
    par(ask=TRUE)

    boxplot(blinds$response,controls$response,
        names=c("blinds","controls"),
        ylab="Response",main=paste("Plate ",plate))
    
    drdata <- platedata[c(2,4,6)]
    drdata$substance <- factor(drdata$substance)
    substances <- levels(drdata$substance)
       
    plot(log10(drdata$conc),drdata$viability,
        xlim=c(-2.5, 4.5), 
        ylim= c(-0.1, 2), 
        xlab=paste("decadic logarithm of the concentration in ",levels(platedata$unit)),
        ylab=responsetype)
    
    drdatalist <- split(drdata,drdata$substance)
    
    for (i in 1:length(drdatalist)) {
        points(log10(drdatalist[[i]]$conc),drdatalist[[i]][[responsetype]],col=i);
    }

    legend("topleft",substances, pch=1, col=1:length(substances), inset=0.05)
    title(main=paste("Plate ",plate," - ",
        levels(platedata$experimentator)," - ",levels(platedata$type)))
}

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