segmentation {mpss} | R Documentation |
Performs segmentation by applying a threshold on the intensity values.
segmentation = function(data = data, location = location, chromosome = cc, del.lim = -0.15, dup.lim = 0.15, min.probes = 10, min.probe.density = 5, min.length = 1000, min.dist = 5000, fdr.limit = 1e-05, chi = chi, pos1 = pos1, pos2 = pos2, pos3 = NA, pos4 = NA, data1 = data1, data2 = data2, data3 = NA, data4 = NA)
data |
A list of estimated smoothed intensities, each component corresponding to each chromosome. |
location |
A list of genomic locations that corresponds to each value in intensity. |
chromosome |
A vector of same length as intensity and location that indicates the chromosome number. |
del.lim |
Threshold for deletions. |
dup.lim |
Threshold for duplications. |
min.probes |
Minimum number of probes in region. |
min.probe.density |
Minimum number of probes per kb in region. |
min.length |
Minimum length of region. |
min.dist |
Two regions will be merged if the distance between them is less than min.dist . |
fdr.limit |
Fdr threshold to define significant segments. See Details. |
chi |
A list of contribution of each probe to the chi-squared statistic, each component corresponding to each chromosome. |
pos1 |
Probe positions for platform 1. A list where each component corresponds to each chromosome. |
pos2 |
Same as pos1, but for platform 2. |
pos3 |
Same as pos1, but for platform 3. Set to NA if there is no platform 3 available |
pos4 |
Same as pos1, but for platform 4. Set to NA if there is no platform 4 available. |
data1 |
Normalized intensity ratio for platform 1, corresponding to each position in pos1. A list where each component corresponds to each chromosome. |
data2 |
Same as data1, but for platform 2. |
data3 |
Same as data1, but for platform 3. Set this to NA if there is no platform 3 available. |
data4 |
Same as data1, but for platform 4. Set this to NA if there is no platform 4 available. |
Deletion segments are sets of consecutive probes for which 'intensity' is consistenly smaller than del.lim and duplication segments are sets of consecutive probes for which 'intensity' is consistenly larger than dup.lim.
cnv |
A data frame with 23 columns:
start : Start position of region.
end : End position of region.
chr : Chromosome number of region..
start.loc : Index of start position in unlist(location) .
end.loc : Index of end position in unlist(location) .
length : length of region.
p : p-value.
fdr : false discovery rate.
numprobes : number of probes in region.
scaled_x2 : scaled chi squared value.
cn : copy number status, 1 for deletion and 3 for duplication.
m : mean of the probe intensities in the region.
sd : standard deviation of the probe intensities in the region.
pt : p value for test of discrepant regions. See Teo et al., 2010 for details.
t_fdr : FDR for test of discrepant regions. See Teo et al., 2010 for details.
m1 : mean of the probe intensities from platform 1 in the region.
m2 : same as m1 but for platform 2.
m3 : same as m1 but for platform 3.
m4 : same as m1 but for platform 4.
sd1 : standard deviation of the probe intensities from platform 1 in the region.
sd2 : same as sd1 but for platform 2.
sd3 : same as sd1 but for platform 3.
sd4 : same as sd1 but for platform 4.
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Teo S M et al.,(2010). Multi-Platforms Segmentation Approach for Joint Detection of Copy Number Variations. Submitted.
setwd(paste(searchpaths()[grep("mpss",searchpaths())],'/data/',sep="")) load("illum12056.Rdata") #Illumina platform #norm_y contains the normalized intensity ratios for chromosome 1 and 2. #norm_x contains the corresponding probe locations. illum = norm_y illumx = norm_x load("affy12056.Rdata") #Affymetrix platform affy = norm_y affyx = norm_x data = NULL location = NULL chi = NULL for(chr in 1:2){ ss = smoothseg2(pos1 = affyx[[chr]] ,pos2 = illumx[[chr]], pos3 = NA, pos4 = NA, data1 = affy[[chr]], data2 = illum[[chr]], data3 = NA, data4 = NA, maxiter = 50, lambda = 100, lambda.range=c(20,600)) data[[chr]] = ss$y location[[chr]] = ss$pos chi[[chr]] = ss$chi } cc = NULL for (i in 1:2){ cc = c(cc, rep(i, length(location[[i]]))) } s = segmentation(data = data, location = location, chromosome = cc, del.lim = -0.15, dup.lim = 0.15, min.probes = 10, min.probe.density = 5, min.length = 1000, min.dist = 5000, fdr.limit = 1e-05, chi = chi, pos1 = affyx, pos2 = illumx, pos3 = NA, pos4 = NA, data1 = affy, data2 = illum, data3 = NA, data4 = NA)