R: Mixture model for DNA methylation data in cancer.
MethylMix
R Documentation
Mixture model for DNA methylation data in cancer.
Description
MethylMix identifies DNA methylation driven genes by modeling DNA
methylation data in cancer vs. normal and looking for homogeneous
subpopulations. In addition matched gene expression data (e.g. from
microarray technology or RNA sequencing) is used to identify functional
DNA methylation events by requiring a negative correlation between
methylation and gene expression of a particular gene.
This a matrix with the methylation data of cancer tissue
with genes in rows and samples in columns
METnormal
This is a matrix with the normal methylation data of the
same genes as in METcancer. Again genes in rows and samples in columns. The
samples do not have to match with the cancer data.
MAcancer
This is the matched gene expression data for the same
samples as in METcancer.
OutputRoot
Path to store the MethylMix results object.
Parallel
If true MethylMix will be run using parallel processing.
Value
MethylMixResults is a list with the following components:
MethylationStates
Matrix with for all genes the Methylation states
using DM-value (i.e. Differential methylation values) that are defined as
the methylation value with respect to the average normal methylation for a
gene.
NrComponents
The number of methylation states for each gene.
Models
Beta mixture model parameters for each gene.
MethylationDrivers
Genes identified as functional and differential
by MethylMix.
MixtureStates
A list with the DM-values for each gene that is
functional and differential.
Examples
# load the three data sets needed for MethylMix
data(METcancer)
data(METnormal)
data(MAcancer)
# run methylmix on a small set of example data
MethylMixResults=MethylMix(METcancer,METnormal,MAcancer)
# try the parallel toolbox to speed up MethylMix modeling
MethylMixResults=MethylMix(METcancer,METnormal,MAcancer,Parallel=TRUE)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(MethylMix)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/MethylMix/MethylMix.Rd_%03d_medium.png", width=480, height=480)
> ### Name: MethylMix
> ### Title: Mixture model for DNA methylation data in cancer.
> ### Aliases: MethylMix
>
> ### ** Examples
>
>
> # load the three data sets needed for MethylMix
> data(METcancer)
> data(METnormal)
> data(MAcancer)
>
> # run methylmix on a small set of example data
> MethylMixResults=MethylMix(METcancer,METnormal,MAcancer)
Found 251 samples with both methylation and expression data.
Correlating methylation data with gene expression.
| | | 0% | |======== | 8% | |=============== | 15% | |======================= | 23% | |=============================== | 31% | |====================================== | 38% | |============================================== | 46% | |====================================================== | 54% | |============================================================== | 62% | |===================================================================== | 69% | |============================================================================= | 77% | |===================================================================================== | 85% | |============================================================================================ | 92% | |====================================================================================================| 100%
Found 9 functional genes.
Starting Beta mixture modeling.
Running Beta mixture model on 9 functional genes and on 251 samples.
ERBB2 : Two components are best.
FAAH : Two components are best.
FOXD1 : Two components are best.
ME1 : Two components are best.
MGMT : Two components are best.
OAS1 : Two components are best.
SOX10 : Two components are best.
TRAF6 : Two components are best.
ZNF217 : Two components are best.
>
> # try the parallel toolbox to speed up MethylMix modeling
> MethylMixResults=MethylMix(METcancer,METnormal,MAcancer,Parallel=TRUE)
Found 251 samples with both methylation and expression data.
Correlating methylation data with gene expression.
| | | 0% | |======== | 8% | |=============== | 15% | |======================= | 23% | |=============================== | 31% | |====================================== | 38% | |============================================== | 46% | |====================================================== | 54% | |============================================================== | 62% | |===================================================================== | 69% | |============================================================================= | 77% | |===================================================================================== | 85% | |============================================================================================ | 92% | |====================================================================================================| 100%
Found 9 functional genes.
Starting Beta mixture modeling.
Running Beta mixture model on 9 functional genes and on 251 samples.
ERBB2 : Two components are best.
FAAH : Two components are best.
FOXD1 : Two components are best.
ME1 : Two components are best.
MGMT : Two components are best.
OAS1 : Two components are best.
SOX10 : Two components are best.
TRAF6 : Two components are best.
ZNF217 : Two components are best.
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> dev.off()
null device
1
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providing 
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