Description Usage Arguments Value Author(s) Examples
This function generates the final report of the CNV detection procedure. One data frame is generated for each sample of interest.
1 2 3 4 5 | ReportTables(geneNames,
samplesNormalizedReadCounts,
referenceNormalizedReadCounts,
bootList,
backgroundNoise)
|
geneNames |
Describe |
samplesNormalizedReadCounts |
Describe |
referenceNormalizedReadCounts |
Describe |
bootList |
A list as returned by the |
backgroundNoise |
A list of background noise as returned by the
|
Returns a list of tables, one for each sample of interest. Each of these tables contains numerical information of the aberration status of each gene. For a detailed description see the Vignette.
Thomas Wolf, Cristiano Oliveira
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | data(sampleReadCounts)
data(referenceReadCounts)
## Gene names should be same size as row columns
geneNames <- row.names(referenceReadCounts)
ampliconNames <- NULL
normalizedReadCounts <- CombinedNormalizedCounts(sampleReadCounts,
referenceReadCounts,
ampliconNames = ampliconNames)
# After normalization data sets need to be splitted again to perform bootstrap
samplesNormalizedReadCounts = normalizedReadCounts["samples"][[1]]
referenceNormalizedReadCounts = normalizedReadCounts["reference"][[1]]
# Should be used values above 10000
replicates <- 10
# Perform the bootstrap based analysis
bootList <- BootList(geneNames,
samplesNormalizedReadCounts,
referenceNormalizedReadCounts,
replicates = replicates)
backgroundNoise = Background(geneNames,
samplesNormalizedReadCounts,
referenceNormalizedReadCounts,
bootList,
replicates = replicates)
reportTables <- ReportTables(geneNames,
samplesNormalizedReadCounts,
referenceNormalizedReadCounts,
bootList,
backgroundNoise)
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