sequenza
in a standardized pipeline.sequenza.extract(file, gz = TRUE, window = 1e6, overlap = 1, gamma = 80,
kmin = 10, mufreq.treshold = 0.10, min.reads = 40,
max.mut.types = 1, min.type.freq = 0.9) sequenza.fit(sequenza.extract, female = TRUE, segment.filter = 1e7,
XY = c(X = "X", Y = "Y"), cellularity = seq(0.1,1,0.01),
ploidy = seq(1, 7, 0.1), priors.table = data.frame(CN = 2, value = 2),
mc.cores = getOption("mc.cores", 2L))
aspcf
from the copynumber
package.sequenza.extract
function.CN
and value
, containing the copy numbers and the corresponding weights. To every copy number is assigned the value 1 as default, so every values different then 1 will change the corresponding weight.parallel
package.sequenza.extract
utilizes a range of functions from the sequenza package to read the raw data, normalize the depth.ratio for GC-content bias, perform allele-specific segmentation, filter for noisy mutations and binning of the raw data for plotting. The computed objects are returned as a single list object. This object can be given to sequenza.fit
, which uses baf.model.fit
to calculate the log-likelihood for all pairs of the ploidy and cellularity parameters.genome.view
, baf.bayes
, cp.plot
, get.ci
.data.file <- system.file("data", "abf.data.abfreq.txt.gz",
package = "sequenza")
test <- sequenza.extract(data.file)
CP <- sequenza.fit(test, mc.cores = 4)
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