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<p>Page créée avec « ranges [http://www.selleckchem.com/products/RO4929097.html selleck screening library] ( factor (targets$Sample_Group)... »</p> <p><b>Nouvelle page</b></p><div>ranges [http://www.selleckchem.com/products/RO4929097.html selleck screening library] ( factor (targets$Sample_Group))]samps [http://www.selleckchem.com/products/NVP-AUY922.html selleck inhibitor] 1 : nrow (targets) # draw the plot par ( mfrow=c ( 1 , 1 )) DMR.plot ( [https://en.wikipedia.org/wiki/Fleroxacin Fleroxacin] ranges= results.ranges, dmr= 1 , CpGs= bVals, phen.col= cols, pch= 16 , toscale= TRUE , plotmedians= TRUE , genome= &quot;&quot;hg19&quot;&quot; , samps= samps) Customising visualisations of methylation data The Gviz package offers powerful functionality for plotting methylation data in its genomic context. The package vignette is very extensive and covers the various types of plots that can be produced using the Gviz framework. We will re-plot the top differentially methylated region from the DMRcate regional analysis to demonstrate the type of visualisations that can be created ( Figure 11). Figure 11. The Gviz package provides extensive functionality for customising plots of genomic regions. We will first set up the genomic region we would like to plot by extracting the genomic coordinates of the top differentially methylated region.</div>

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