#Load the bias-corrected version of the Wilms' tumor copy number data
wilmsdata.nobias = read.table("http://www.bios.unc.edu/research/genomic_software/DiNAMIC/wilmsdata.nobias.txt", sep = "\t", header = FALSE)
wilmsdata.nobias = as.matrix(wilmsdata.nobias)

#Load Wilms' tumor marker data
wilms.markers = read.table("http://www.bios.unc.edu/research/genomic_software/DiNAMIC/wilms.markers.txt", sep = "\t", header = TRUE)

#Load cytoband annotation file
annot.file = read.table("http://www.bios.unc.edu/research/genomic_software/DiNAMIC/annot.file.txt", sep = "\t")
annot.file = as.matrix(annot.file)

#Define other input parameters
num.perms = 100 	#Number of cyclic shifts used to create the null distribution
num.iters = 10	#Number of aberrant markers assessed

#Use the Detailed Look procedure to assess the significance of the 10 most aberrant markers in the
#bias-corrected version of the Wilms' tumor data
try.it = detailed.look(wilmsdata.nobias, wilms.markers, annot.file, num.perms, num.iters, 
	gain.loss = "gain", random.seed = NULL)

try.it[[1]]

try.it[[2]]

unlist(try.it[[2]][1, 2])

unlist(try.it[[2]][1, 3])[178:179]

#Use the Quick Look procedure to assess the significance of the 10 most aberrant markers in the
#bias-corrected version of the Wilms' tumor data
try.it.again = quick.look(wilmsdata.nobias, wilms.markers, annot.file, num.perms, num.iters,
	gain.loss = "gain", random.seed = 12345)

try.it.again[[1]]