scanone and using a genetical exclusionary window.
define.peak(scanone,lodcolumn=1,chr,th=2.3,si=1.5,graph=FALSE,window.size=20,
round,save.pict=FALSE, phe.name, ...)"all" which indicates all LOD score columns. This can also be a vector of integers indicating which of the columns should be used or a strings vector matching the names of the LOD columns, the phenotypes' name, to analyse. See qtl package manual for scanone function details.si is the value of the accepted drop of LOD score to estimate the likely region on which the QTL is localized.TRUE, draws the LOD curve with LOD peaks and support interval for the detected QTLs.TRUE, save the LOD curves drawn with support interval as png files named like "trait name"\_"chromosome"\_"a number".png in the current folder.round function for details.scanone on a single trait, the lodcolumn is named 'lod' and as the analysed trait.plot and plot.scanone when they are called (if graph=TRUE). Passed the maximum size of the genomic region parameter: m=10 should set 2*10cM for the inferior and the superior SI bounds from the position of the peakpeak which is a list of components corresponding to traits. names(peak) contains the names of the traits. Each trait is itself a list with elements corresponding to chromosomes. For chromosomes on which no QTL have been detected, peak\$trait\$chromosome contains a NA value (where chromosome is the number identifying the chromosome). For those on which a QTL has been detected peak\$trait\$chromosome contains a data frame where rows are detected QTLs and columns are peak features (which describe QTLs). names(peak\$trait\$chromosome) contains the peak features:
m). This quality information corresponds to symbols indicating, how each were defined by the bounds of the QTL support interval. The symbols on the right side gives the information for the superior SI bounds and so on for the left sided bounds. '+' indicates that the LOD-drop support interval has been reached. '<-' and '->' indicates that the LOD-drop SI hasn't been reached before the maximum SI size (defined by m argument) for the inferior and the superior bounds respectively. '|' indicates that the LOD-drop SI has been delimited by the beginning or the end of the LOD curve either for the inferior or superior bounds respectively. Therefore, the quality symbols '|->' indicates that the SI has been delimited on the left by the beginning of the LOD curve and on the right by the maximum SI size. Therefore, the drop of LOD score is not reached on either the left or right. '+|' indicates that the SI has been reached on the left but has been delimited on the right by the end of the LOD curve. Symbols -"++" -"<-->" -m parameter. The SI is not reached."+|" -"|+" -"<-|" -m/2 on the left."|->" -m/2 on the right.scanone function.
A QTL is considered as a genomic region defined by a maximum LOD score peak value, its position and the position of its support interval (here called dQuoteSI). The SI is estimated by the accepted drop of LOD score from the maximum LOD value defining the QTL region (the LOD peak). The FDR falls as the QTL SI size increases with lower LOD scores away from the peak. Usually we use si=1.5 or si=2. A genetic exclusionary window sets the minimum distance between two distinct QTLs which we consider being able to detect and depends directly on the size of the population. Due to the shape of the LOD curve, the drop of LOD score cannot be reached in some cases. Therefore a maximum SI size is set at 20 cM by default. m=10 will set 2*10cM for the inferior and the superior SI bounds. graph=TRUE specify to draw the LOD curves and the LOD SI on different chart for each QTL on their chromosome. No graphical setup has been defined and therefore they will be drawn one above the other in the same R graphical window. To setup the graph page and print all the charts in same window, one may use the graphical parameter mfrow of the R function par() according specific needs before launching define.peak. You may not want to set graph=TRUE and lodcolumn="all" at the same time depending on the amount of data. The parameter save.pict is useful to save systematically all charts generated by define.peak. These graphs are already page setted by the usual graphical functions (like mfrow).
scanone,read.crossdata(seed10);
out.em <- scanone( seed10, pheno.col=1:50, model='normal', method='hk');
################################################
# Detecting QTL with LOD drop support interval #
################################################
# Defining QTLs for all traits and saving the curves in png files.
out.peak <- define.peak(out.em, 'all',graph=TRUE,save.pict=TRUE,round=3);
# Defining QTLs for few traits and drawing the curves.
par(mfrow=c(1,5));
out.peak <- define.peak(out.em,lodcolumn=c(3,4,40,49),graph=TRUE,round=3);
par(mfrow=c(1,1));
# Defining QTLs for one trait and drawing the curves.
out.peak <- define.peak(out.em,lodcolumn='CATrck',graph=TRUE,round=3);
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