displayHTS (version 1.0)

plateWellSeries.fn: Plate-Well Series Plot

Description

Function that draws a plate-well series plot for all or part of plates.

Usage

plateWellSeries.fn(data.df, intensityName = NA, plateName = "BARCODE", wellName = "WELL_USAGE", rowName, colName, show.wellTypes = NULL, order.wellTypes = NULL, color.wells = NULL, pch.wells = NULL, ppf = 12, byRow = T, yRange = NULL, cex.point = 0.25, cex.legend = 0.3, x.legend = NA, y.legend = NA, main = NA, xlab = NA, ylab = NA)

Arguments

data.df

The data for all plates including at least five columns for intensity, plate names, well names, rows, and columns, respectively.

intensityName

Name of the column in data.df indicating intensities in a plate.

plateName

Name of the column in data.df indicating plate names.

wellName

Name of the column in data.df indicating well types.

rowName

Name of the column in data.df indicating row numbers in a plate.

colName

Name of the column in data.df indicating column numbers in a plate.

show.wellTypes

A vector of well types to be shown in the well-series plot.

order.wellTypes

A vector of numbers to indicate the order of well types corresponding to 'show.wellTypes' in the well-series plot.

color.wells

A vector indicating the colors of well types corresponding to 'show.wellTypes' in the well-series plot.

pch.wells

A vector indicating the point types of well types corresponding to 'show.wellTypes' in the well-series plot.

ppf

The number of plates per figure to be shown in the well-series plot.

byRow

Indicates whether the wells in a plate should be shown by row or column.

yRange

Defines the range of the y-axis in the well-series plot.

cex.point

Defines the size of points in the well-series plot.

cex.legend

Defines the size of legend in the well-series plot.

x.legend

Position of legend on x-axis.

y.legend

Position of legend on y-axis.

main

Title of the image.

xlab

The label for the x-axis.

ylab

The label for the y-axis.

References

Zhang XHD, Zhang ZZ. 2013. displayHTS: a R package displaying data and results from high-throughput screening experiments. Bioinformatics (submitted). Zhang XHD, 2011. Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-scale RNAi Research. Cambridge University Press, Cambridge, UK. Zhang XHD, Yang XC, Chung N, Gates AT, Stec EM, Kunapuli P, Holder DJ, Ferrer M, Espeseth AS. 2006. Robust statistical methods for hit selection in RNA interference high throughput screening experiments. Pharmacogenomics 7 (3) 299-309.

See Also

imageDesign.fn, imageIntensity.fn, dualFlashlight.fn

Examples

   data(HTSdataSort)
   wells = as.character(unique(HTSdataSort[, "WELL_USAGE"])); wells
   colors = c("black",  "yellow", "grey", "blue", "skyblue", "green", "red")
   orders=c(1, 3, 2, 4, 5, 7, 6)
   # by row
   par( mfrow=c(2,1) )                                                        
   plateWellSeries.fn(data.df = HTSdataSort, intensityName="log2Intensity",
                      plateName="BARCODE", wellName="WELL_USAGE",              
                      rowName="XPOS", colName="YPOS", show.wellTypes=wells,
                      order.wellTypes=orders, color.wells=colors,
                      pch.wells=rep(1, 7), ppf=6, byRow=TRUE,  
                      yRange=NULL, cex.point=0.25,cex.legend=0.3) 
   # by column
   par( mfrow=c(2,1) )                                                        
   plateWellSeries.fn(data.df = HTSdataSort, intensityName="log2Intensity",
                      plateName="BARCODE", wellName="WELL_USAGE",              
                      rowName="XPOS", colName="YPOS", show.wellTypes=wells,
                      order.wellTypes=orders, color.wells=colors,
                      pch.wells=rep(1, 7), ppf=6, byRow= FALSE,  
                      yRange=NULL, cex.point=0.25,cex.legend=0.3) 
   # display hits
   data(HTSresults)
   condtSample = HTSresults[, "WELL_USAGE"] == "Sample"
   condtUp = HTSresults[,"ssmd"] >= 1 & HTSresults[,"mean"] >= log2(1.2)
   condtDown = HTSresults[,"ssmd"] <= -1 & HTSresults[,"mean"] <= -log2(1.2)
   sum(condtSample & (condtUp | condtDown) )/sum(condtSample)
   hit.vec = as.character(HTSresults[, "WELL_USAGE"])
   hit.vec[ condtSample & condtUp ] = "up-hit"
   hit.vec[ condtSample & condtDown ] = "down-hit"
   hit.vec[ condtSample & !condtUp & !condtDown] = "non-hit"
   result.df = cbind(HTSresults, "hitResult"=hit.vec)
   wells = as.character(unique(result.df[, "hitResult"])); wells
   orders = c(1, 3, 4, 6, 7, 8, 9, 2, 5) 
   colors = c("black",  "green", "yellow", "red",
              "grey", "purple1", "purple2", "lightblue", "purple3")
   par(mfrow=c(1,1))
   plateWellSeries.fn(data.df = result.df, intensityName="mean",       
                      plateName="SOBARCODE", wellName="hitResult", 
                      rowName="XPOS", colName="YPOS", show.wellTypes=wells,
                      order.wellTypes=orders, color.wells=colors,
                      pch.wells=rep(1, 7), ppf=6, byRow= FALSE,  
                      yRange=NULL, cex.point=0.5,cex.legend=0.55,
                      y.legend=-0.5)