GenomicReports         package:beadarraySNP         R Documentation

_G_e_n_o_m_i_c _r_e_p_o_r_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     create reports for all samples in a dataset

_U_s_a_g_e:

     reportChromosomesSmoothCopyNumber(snpdata, grouping, normalizedTo = 2, 
       smooth.lambda = 2, ridge.kappa = 0, plotLOH = c("none", "marker", "line", "NorTum"), ...)
     reportSamplesSmoothCopyNumber(snpdata, grouping, normalizedTo = 2, 
       smooth.lambda = 2, ridge.kappa = 0, plotLOH = c("none", "marker", "line", "NorTum"), ...)
     reportGenomeGainLossLOH(snpdata, grouping, plotSampleNames=FALSE, distance.min,
       upcolor="red", downcolor="blue", lohcolor="grey", hetcolor="lightgrey", lohwidth=1,segment=101,
       orientation=c("V","H"),...)
     reportChromosomeGainLossLOH(snpdata,grouping,plotSampleNames=FALSE,distance.min,
       upcolor="red", downcolor="blue", lohcolor="grey", hetcolor="lightgrey", proportion=0.2, plotLOH=TRUE,
       segment=101,...)  
     reportGenomeIntensityPlot(snpdata,normalizedTo=NULL,subsample=NULL,col="black",...)

_A_r_g_u_m_e_n_t_s:

 snpdata: SnpSetIllumina object

grouping: factor, elements with same value are plotted together.
          Defaults to groups of 4 in order of the samples in the object

normalizedTo: numeric, a horizontal line is drawn at this position

smooth.lambda: smoothing parameter for 'quantsmooth'

ridge.kappa: smoothing parameter for 'quantsmooth'

 plotLOH: indicate regions or probes with LOH, see details

plotSampleNames: logical

distance.min: numerical

 upcolor: color

downcolor: 

lohcolor: 

hetcolor: 

lohwidth: 

 segment: 

orientation: 

proportion: 

subsample: 

     col: 

     ...: arguments are forwarded to 'plot' or 'getChangedRegions'

_D_e_t_a_i_l_s:

     The first function creates plots for each group and each
     chromosome in the  dataset. The second function creates full
     genome plot for each group in the dataset. Beware that a lot of
     plots can be created, and usually you should  prepare for that, by
     redirecting the plots to 'pdf' or functions that create picture
     files like 'jpg, png, bmp'

_V_a_l_u_e:

_A_u_t_h_o_r(_s):

     Jan Oosting

_S_e_e _A_l_s_o:

     'quantsmooth','prepareGenomeplot',
     'pdfChromosomesSmoothCopyNumber', 'pdfSamplesSmoothCopyNumber'

_E_x_a_m_p_l_e_s:

     data(chr17.260)
     chr17nrm<-standardNormalization(chr17.260)
     par(mfrow=c(4,2),mar=c(2,4,2,1))
     reportChromosomesSmoothCopyNumber(chr17nrm, grouping=pData(chr17.260)$Group,smooth.lambda = 4)

