normalizeFragmentData: Normalize near-cis fragment data read count
In Basic4Cseq: Basic4Cseq: an R/Bioconductor package for analyzing 4C-seq data
Description
Usage
Arguments
Value
Author(s)
Examples
Description
This function provides a simple RPM (reads per million) normalization for near-cis fragment data read counts of a Data4Cseq object. A form of normalization is especially important for the comparison of samples with a different read count.
Usage
1
normalizeFragmentData(expData)
Arguments
expData
Experiment data of class Data4Cseq with information on the 4C-seq experiment
Value
Data frame with RPM-normalized data
Author(s)
Carolin Walter
Examples
1
2
3
data(liverDataRaw)
normalizedFragments<-normalizeFragmentData(liverDataRaw)
head(normalizedFragments)
Basic4Cseq documentation built on Nov. 8, 2020, 6:53 p.m.
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Description Usage Arguments Value Author(s) Examples
Description
This function provides a simple RPM (reads per million) normalization for near-cis fragment data read counts of a Data4Cseq object. A form of normalization is especially important for the comparison of samples with a different read count.
Usage
1 | normalizeFragmentData(expData)
|
Arguments
expData |
Experiment data of class |
Value
Data frame with RPM-normalized data
Author(s)
Carolin Walter
Examples
1 2 3 | data(liverDataRaw)
normalizedFragments<-normalizeFragmentData(liverDataRaw)
head(normalizedFragments)
|
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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