diffMethylData: Randomly generated nucleotide-resolution methylation signal...
In MethylCapSig: Detection of Differentially Methylated Regions using MethylCap-Seq Data
Description
Usage
Format
References
Description
Nucleotide resolution methylation-signal data for two groups of samples. The signals are randomly generated and to mimic acute myeloid cancer data set studied by Frankhouser et al. (2014). Signals are reported for two regions - region1 with 92 CpG sites and region2 with 122 CpG sites. While region1 is known to be non-differentially methylated, region2 is differentially methylated. Sample sizes for the two groups are 20 and 10 respectively.
Usage
1
Format
A data frame with signal matrices for two groups recorded on two regions.
region1.xa 20 \times 92 matrix
region1.ya 10 \times 92 matrix
region1.xa 20 \times 122 matrix
region1.ya 10 \times 122 matrix
References
Frankhouser, D. E., et al. (2014) PrEMeR-CG: inferring nucleotide leve DNA methylation values from MethylCap-seq data, Bioinformatics, 30 (24), 3567 – 3574.
Ayyala, D. N., et al. (2015) Statistical methods for detecting differentially methylated regions based on MethylCap-Seq data, Manuscript.
MethylCapSig documentation built on May 2, 2019, 9:24 a.m.
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Description Usage Format References
Description
Nucleotide resolution methylation-signal data for two groups of samples. The signals are randomly generated and to mimic acute myeloid cancer data set studied by Frankhouser et al. (2014). Signals are reported for two regions - region1 with 92 CpG sites and region2 with 122 CpG sites. While region1 is known to be non-differentially methylated, region2 is differentially methylated. Sample sizes for the two groups are 20 and 10 respectively.
Usage
1 |
Format
A data frame with signal matrices for two groups recorded on two regions.
region1.xa 20 \times 92 matrix
region1.ya 10 \times 92 matrix
region1.xa 20 \times 122 matrix
region1.ya 10 \times 122 matrix
References
Frankhouser, D. E., et al. (2014) PrEMeR-CG: inferring nucleotide leve DNA methylation values from MethylCap-seq data, Bioinformatics, 30 (24), 3567 – 3574.
Ayyala, D. N., et al. (2015) Statistical methods for detecting differentially methylated regions based on MethylCap-Seq data, Manuscript.
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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