normMethod | R Documentation |
This function allows to define normalization methods by specifying components.
normMethod(methods, ...)
methods |
names of predefined normalization methods ( for a list of predefined methods, see details) |
... |
sets of normalization components, that can be combined to user defined normalization methods |
Predefined normalization methods:
“counts”: no normalization, simply raw count values
“reads”: same as counts
“rpm”: reads per million mappable reads
“nrpm”: CNV normalized reads per million mappable reads
“beta”: transformation to % methylation, posterior mean point estimator
“logitbeta”: logit transformed beta values
“betaLB”: 2.5 lower bound for the point estimator
“betaUB”: 97.5 upper bound for the point estimator
Allowd components for user defined normalization methods:
“library_size”: scale by effective library size
“region_length”: scale by window size
“preference”: scale by positional sequencing preference
“cnv”: scale by CNV ratio
“enrichment”: use enrichment profiles for transformation to absolute methylation level
“qXY”: quantile estimator for transformation to absolute methylation level. XY must be replaced by the quantile (see example with self defined lower and upper bound)
“offset”: consider background reads
WARNING: not all combinations are allowed (eg qXY requires enrichment) and not all allowed combinations are meaningful. Inexperienced users should stick to predefined normalization methods.
a list object, containing the components for the specified normalization procedure
Mathias Lienhard
makeTable
#simply raw counts
nm=normMethod("counts")
#beta-values (% methylation) including lower and upper bounds
nm=normMethod(c("beta", "betaLB", "betaUB"))
#self defined lower and upper bound: 10% and 90% quantile
nm=normMethod("beta",
betaLB_10=c("enrichment", "cnv", "library_size",
"region_length", "preference","q10", "offset"),
betaUB_90=c("enrichment", "cnv", "library_size",
"region_length", "preference","q90", "offset")
)
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