Description Details Fields Methods See Also
A ReferenceClass that contains all the data needed and generated by the RUBIC algorithm.
It is possibile and recommended to instanciate a new RUBIC object by using the
convenience function rubic
.
fdr
Event based false descovery rate.
genes
A data.table containg the gene locations.
samples
A character vector containing sample IDs.
markers
A data.table containing the markers informations.
map.loc
A data table containing the markers mapped on the segments.
min.mean
The minimum mean copy number allowed.
max.mean
The maximum mean copy number allowed.
min.probes
The minimum number of probes to be considered in the analysis.
min.seg.markers
The number of probes allowed in each segment.
amp.level
The threshold used for calling amplifications.
del.level
The threshold used for calling deletions.
focal.threshold
The maximum length of a recurrent region to be called focal.
call.events()
Call recurrent events.
call.focal.events(genes = NULL)
Call focal events.
estimate.parameters(quiet = T, test.env = NULL)
Estimate the parameters necessary for segmentation and event calling.
initialize(fdr = NULL, seg.cna = NULL, markers = NULL, samples = NULL,
genes = NULL, amp.level = 0.1, del.level = -0.1, min.seg.markers = 1,
min.mean = NA_real_, max.mean = NA_real_, min.probes = 260000,
focal.threshold = 1e+07, seg.cna.header = T, markers.header = T,
samples.header = F, col.sample = 1, col.chromosome = 2, col.start = 3,
col.end = 4, col.log.ratio = 6, ...)
Create a new RUBIC object. It is recommended to use the rubic function instead of calling this method directly. See rubic for parameter descriptions.
save(file)
Save the current state of the RUBIC object to file.
save.focal.gains(file)
Save focal gains to a file in TSV format.
save.focal.losses(file)
Save focal losses to a file in TSV format.
save.plots(dir, genes = NULL, steps = T, width = 11, height = 5)
Save gains and losses plots for each chromosome.
segment()
Generate positive and negative segments.
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