Directly known subclasses:
public static class SpotData
Creates an SpotData object. If the data frame
data is empty or
NULL, the object will be empty.
| ||Gets (an approximation of) the standard deviation of the foreground pixels.|
| ||Gets the standard error of the foreground pixels.|
| ||Gets the raw intensites from the SpotData structure.|
| ||Gets physical positions of the spots.|
| ||Creates a spatial plot of a slide.|
| ||Reads several Spot files into a SpotData object.|
| ||Write a SpotData 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 Spot file contains spot information for each spot on a single microarray slide. It consists of a header followed by a unspecified number of rows. The header contains 1+30 labels, and each row contains 31 fields. Each row corresponds to one spot. The fields are:
<NO NAME>row number\item
indexsspot number on slide. Range [0,N] in N.\item
grid.rgrid row number. Range [1,GR] in Z+. \itemgrid.cgrid column number. Range [1,GC] in Z+. \itemspot.rspot row (within grid) number. Range [1,SR] in Z+. \itemspot.cspot column (within grid) number. Range [1,SC] in Z+.\item
areathe number of foreground pixels. Range [0,MAXAREA] in N\item
Gmeanthe average of the foreground pixel values. Range [0,65535] in R \itemGmedianthe median of the foreground pixel values. Range [0,65535] in N \itemGIQRthe inter quartile range (a robust measure of spread) of the logged foregroud pixel values. Range [0,16]+Inf in R,NA \itemRmeanthe average of the foreground pixel values. Range [0,65535] in R \itemRmedianthe median of the foreground pixel values. Range [0,65535] in N \itemRIQRthe inter quartile range (a robust measure of spread) of the logged foregroud pixel values. Range [0,16]+Inf in R,NA\item
bgGmeanmean green background intesity. Range [0,65535] in R \itembgGmedmedian green background intesity. Range [0,65535] in N \itembgGSDstandard deviation for the green background. Range [0,65535]+Inf in R \itembgRmeanmean red background intesity. Range [0,65535] in R \itembgRmedmedian red background intesity. Range [0,65535] in N \itembgRSDstandard deviation for the red background. Range [0,65535]+Inf in R\item
valleyGthe background intesity estimate from the local background valley method S.valley. Range [0,65535] in N \itemvalleyRthe background intesity estimate from the local background valley method S.valley. Range [0,65535] in N\item
morphGgreen background estimate using morphological opening (erosion-dilation). Range [0,65535] in N \itemmorphG.erodegreen background estimate using morphological erosion. Range [0,65535] in N \itemmorphG.close.opengreen background estimate using morphological closing-opening (dilation-erosion-dilation). Range [0,65535] in N \itemmorphRred background estimate using morphological opening (erosion-dilation). Range [0,65535] in N \itemmorphR.erodered background estimate using morphological erosion. Range [0,65535] in N \itemmorphR.close.openred background estimate using morphological closing-opening (dilation-erosion-dilation). Range [0,65535] in N\item
logratio== log((Rmedian-morphR)/(Gmedian-morphG), base=2), i.e. Redundant.
\itemperimeter== 2*sqrt(pi*area/circularity), i.e. Redundant.
\itemcircularityShape of spot defined as 4*pi*area/perimeter**2.
\itembadspotIf the spot area is greater than product of the horizontal and the vertical average spot separations, equal to
The interquartile range (IQR) is the distance between the 75%
quantile (percentile) and the 25% quantile.
In words, IQR is the range of the mid 50%. Thus, no outliers are
included in the measure, which is why we say it is a robust measure.
For norammly distributed data IQR = 1.35*σ, where σ
is the standard deviation.
The Spot software provides several different kinds of background estimates where three of them are
based on morphological methods. For all of these methods, the signal selected to be the background
signal is the pixel value at the center of the spot after applying the morphological transform
using a square mask with side 2.5 times the average distance between two spots.
The first and also the simpliest transform (
morph.erode) performs a single erosion step.
The second transform (
morph) performs an opening, which is an erosion followed by
The third transform (
morph.close.open) performs a closing followed by an opening,
which is the same as doing a dilution, then an erosion and a dilution again.
As the names of the steps indicate, an erosion makes the signal smaller and the dilution the signal
larger. Hence, background estimated based on these three methods can always be ordered as
morph.erode <= morph <= morph.close.open.
Henrik Bengtsson (http://www.braju.com/R/)
Spot Software package by CSIRO, Australia, http://www.cmis.csiro.au/iap/spot.htm
Spot: Description of Output, 2003 http://www.cmis.csiro.au/iap/Spot/spotoutput.htm
Y.H. Yang, M. Buckley, S. Dudoit, T. Speed, Comparison of methods for image analysis on cDNA microarray data, Tech. Report 584, Nov 2000. http://www.stat.berkeley.edu/users/terry/zarray/Html/image.html
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spot <- SpotData$read("spot123.spot", 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 <- as.RGData(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)
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