dyeBiasCorrMostBalanced: Correct dye bias using most balanced sample as the reference
In sesame: Tools For Analyzing Illumina Infinium DNA Methylation Arrays
Description
Usage
Arguments
Value
Examples
Description
The function chose the reference signal level from a list of SigSet.
The chosen sample has the smallest difference in Grn and Red signal
intensity as measured using the normalization control probes. In practice,
it doesn't matter which sample is chosen as long as the reference level
does not deviate much. The function returns a list of SigSets with
dye bias corrected.
Usage
1
dyeBiasCorrMostBalanced(ssets)
Arguments
ssets
a list of normalized SigSets
Value
a list of normalized SigSets
Examples
1
2
ssets <- sesameDataGet('HM450.10.TCGA.BLCA.normal')
ssets.db <- dyeBiasCorrMostBalanced(ssets)
sesame documentation built on Nov. 15, 2020, 2:08 a.m.
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Description Usage Arguments Value Examples
Description
The function chose the reference signal level from a list of SigSet.
The chosen sample has the smallest difference in Grn and Red signal
intensity as measured using the normalization control probes. In practice,
it doesn't matter which sample is chosen as long as the reference level
does not deviate much. The function returns a list of SigSets with
dye bias corrected.
Usage
1 | dyeBiasCorrMostBalanced(ssets)
|
Arguments
ssets |
a list of normalized |
Value
a list of normalized SigSets
Examples
1 2 | ssets <- sesameDataGet('HM450.10.TCGA.BLCA.normal')
ssets.db <- dyeBiasCorrMostBalanced(ssets)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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