callBins | R Documentation |
Call aberrations from segmented copy number data.
callBins(object, organism=c("human", "other"), method=c("CGHcall", "cutoff"),
cutoffs=log2(c(deletion = 0.5, loss = 1.5, gain = 2.5, amplification = 10)/2), ...)
object |
An object of class QDNAseqCopyNumbers |
organism |
Either “human” or “other”, see manual page
for |
method |
Calling method to use. Options currently implemented are: “CGHcall” or “cutoff”. |
cutoffs |
When method=“cutoff”, a numeric vector of (log2-transformed) thresholds to use for calling. At least one positive and one negative value must be provided. The smallest positive value is used as the cutoff for calling gains, and the negative value closest to zero is used as the cutoff for losses. If a second positive value is provided, it is used as the cutoff for amplifications. And if a second negative value is provided, it is used as the cutoff for homozygous deletions. |
... |
Additional arguments passed to |
By default, chromosomal aberrations are called with CGHcall. It has been developed for the analysis of series of cancer samples, and uses a model that contains both gains and losses. If used on a single sample, or especially only on a subset of chromosomes, or especially on a single non-cancer sample, it may fail, but method “cutoff” can be used instead.
When using method “cutoff”, the default values assume a uniform cell population and correspond to thresholds of (assuming a diploid genome) 0.5, 1.5, 2.5, and 10 copies to distinguish between homozygous deletions, (hemizygous) losses, normal copy number, gains, and amplifications, respectively. When using with cancer samples, these values might require adjustments to account for tumor cell percentage.
Returns an object of class QDNAseqCopyNumbers
with calling
results added.
Ilari Scheinin
Internally, CGHcall
and ExpandCGHcall
of
the CGHcall package are used when method=“CGHcall”.
data(LGG150)
readCounts <- LGG150
readCountsFiltered <- applyFilters(readCounts)
readCountsFiltered <- estimateCorrection(readCountsFiltered)
copyNumbers <- correctBins(readCountsFiltered)
copyNumbersNormalized <- normalizeBins(copyNumbers)
copyNumbersSmooth <- smoothOutlierBins(copyNumbersNormalized)
copyNumbersSegmented <- segmentBins(copyNumbersSmooth)
copyNumbersSegmented <- normalizeSegmentedBins(copyNumbersSegmented)
copyNumbersCalled <- callBins(copyNumbersSegmented)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.