SpotfinderData: The SpotfinderData class
In HenrikBengtsson/aroma: An R Object-oriented Microarray Analysis package

Description Usage Arguments Fields and Methods Details Information about spot QC flags Author(s) References Examples

Package: aroma
Class SpotfinderData

Object
~~|
~~+--MicroarrayData
~~~~~~~|
~~~~~~~+--SpotfinderData

Directly known subclasses:

public static class SpotfinderData
extends MicroarrayData

Creates an SpotfinderData object. If the data frame data is empty or NULL, the object will be empty.

1	SpotfinderData(layout=NULL)

layout

A Layout object specifying the spot layout of the slides in this data set.

Methods:

	`append`	-
	`as.RawData`	-
	`extractLayout`	-
	`getArea`	-
	`getBackground`	-
	`getBgArea`	-
	`getCircularity`	-
	`getForeground`	-
	`getPerimeter`	-
	`getRawData`	Gets the raw intensites from the SpotfinderData structure.
	`getSNR`	-
	`normalizeGenewise`	-
	`plotSpatial`	Creates a spatial plot of a slide.
	`plotSpatial3d`	-
	`read`	Reads several Spotfinder/TAV files into a SpotfinderData object.
	`write`	Write a SpotfinderData object to file.

Methods inherited from MicroarrayData:
addFlag, append, applyGenewise, applyGroupwise, applyPlatewise, applyPrintdipwise, applyPrinttipwise, as.character, as.data.frame, boxplot, clearCache, clearFlag, createColors, dataFrameToList, equals, extract, getBlank, getCache, getChannelNames, getColors, getExcludedSpots, getExtra, getExtreme, getFieldNames, getFlag, getInclude, getLabel, getLayout, getProbeWeights, getSignalWeights, getSlideNames, getSlidePairs, getSpotPosition, getSpotValue, getTreatments, getView, getWeights, getWeightsAsString, hasExcludedSpots, hasLayout, hasProbeWeights, hasSignalWeights, hasWeights, highlight, hist, isFieldColorable, keepSlides, keepSpots, listFlags, lowessCurve, nbrOfDataPoints, nbrOfFields, nbrOfSlides, nbrOfSpots, nbrOfTreatments, normalizePlatewise, normalizePrintorder, normalizeQuantile, plot, plotDensity, plotGene, plotPrintorder, plotReplicates, plotSpatial, plotSpatial3d, plotXY, points, putGene, putSlide, qqnorm, quantile, range, range2, read, readHeader, readToList, removeSlides, removeSpots, resetProbeWeights, resetSignalWeights, select, seq, setCache, setExcludedSpots, setExtra, setFlag, setLabel, setLayout, setProbeWeights, setSignalWeights, setSlideNames, setTreatments, setView, setWeights, size, str, subplots, summary, text, updateHeader, validateArgumentChannel, validateArgumentChannels, validateArgumentGroupBy, validateArgumentSlide, validateArgumentSlides, validateArgumentSpotIndex, validateArgumentWeights, write, writeHeader

Methods inherited from Object:
$, $<-, [[, [[<-, as.character, attach, attachLocally, clearCache, clone, detach, equals, extend, finalize, gc, getEnvironment, getFields, getInstanciationTime, getStaticInstance, hasField, hashCode, ll, load, objectSize, print, save

A Spotfinder/TAV (TIGR Array Viewer) file is a headerless tab-delimited file with file extension *.tav, which the following contains 8 or 17 columns:

The first eigth column do always exist:
\item1spot row number. Range [0,ROWS] in Z+. \item2spot column number. Range [0,COLS] in Z+. \item3spot metarow/subrow number. Range [0,MROWS] in Z+. \item4spot metacolumn/subcolumn number. Range [0,MCOLS] in Z+. \item5spot row number in a block/grid. Range [0,GROWS] in Z+. \item6spot column number in a block/grid. Range [0,GCOLS] in Z+. \item7spot (integrated) intensity in channel A corrected for (median local) background. Note that saturated pixels are not used for calculations of intensities as they can skew the results. Range [0,MAXAREA*65535] in Z+. \item8spot (integrated) intensity in channel B corrected for (median local) background. Note that saturated pixels are not used for calculations of intensities as they can skew the results. Range [0,MAXAREA*65535] in Z+.

Column 9-17 exists only in full TAV files:
\item9spot mean ratio. Range [0,?] in R+. == (Col 7)/(Col 8), i.e. Redundant.

\item

10spot total area in pixels. Range [0,MAXAREA] in Z+. \item11spot non-saturation factor. This measure shows the percentage of non-saturated pixels in the spot used for integration, i.e. values close to zero means a lot of saturation and values close to one means little saturation. Saturated pixels are not used for calculations of intensities as they can skew the results. Range [0,1] in R. \item12spot median ratio = (median(signalA)-median(bkgA))/(median(signalB)-median(bkgB)). Range [0,MAXRATIO] in R. \item13spot mode ratio = mode(signalA)-mode(nkgA))/(mode(signalB)-mode(bkgB)). Range [0,MAXRATIO] in R. \item14total spot background in channel A =(median(BkgA)* spotarea). This background was subtracted when the spot intensity was calculated. The background is calculated by measuring the average local background and multiplying it by the spot area. Range [0,MAXAREA*65535] in Z+. \item15total spot background in channel B =(median(BkgB)* spotarea). This background was subtracted when the spot intensity was calculated. The background is calculated by measuring the average local background and multiplying it by the spot area. Range [0,MAXAREA*65535] in Z+. \item16spot flag in channel A. This flag is set by QC filter. Range: {A,B,C,X,Y,Z}. \item17spot flag in channel B. This flag is set by QC filter.Range: {A,B,C,X,Y,Z}.

The foreground estimates for channel A (B) can be obtained as the sum of column 7 and 14 (column 8 and 14).

Flag values are generated based on next conditions: \itemAnumber of non-saturated pixels in spot is 0. Redundant \itemBnumber of non-saturated pixels in spot is between 0 and 50. Redundant \itemCnumber of non-saturated pixels in spot is more then 50. Redundant \itemXspot was detected and rejected based on spot shape and spot intensity relative to surrounding background. \itemYspot background is higher than spot intensity. Redundant \itemZspot was not detected by the program. Redundant

Henrik Bengtsson (http://www.braju.com/R/)

TIGR Spotfinder Software, The Institute for Genomic Research, USA, http://www.tigr.org/software/tm4/

## Not run: 
  sf <- SpotfinderData$read("sf111.tav", path=system.file("data-ex", package="aroma"))

  # Get the foreground and the background (and the layout)
  raw <- getRawData(spot)

  # The the background corrected data
  ma <- getSignal(raw, bgSubtract=FALSE)

  subplots(4, ncol=2)

  # Plot R vs G with a lowess line through the data points
  rg <- getRGData(ma)
  plot(rg)
  lowessCurve(rg, lwd=2, gridwise=TRUE)

  # Plot M vs A with a lowess line through the data points
  plot(ma)
  lowessCurve(ma, lwd=2, gridwise=TRUE)

  # Plot spatial
  plotSpatial(ma)

## End(Not run)