View source: R/compute_methQTL.R
doMethQTL | R Documentation |
Function to compute methQTL given DNA methylation and genotyping data.
doMethQTL(
meth.qtl,
sel.covariates = NULL,
p.val.cutoff = 1e-05,
ncores = 1,
cluster.submit = FALSE,
out.dir = getwd(),
default.options = TRUE
)
meth.qtl |
An object of type |
sel.covariates |
Covariates as column names of the sample annotation sheet stored in |
p.val.cutoff |
The p-value cutoff used for methQTL calling |
ncores |
The number of cores used. |
cluster.submit |
Flag indicating if jobs are to be distributed among a SGE compute cluster |
out.dir |
Output directory |
default.options |
Flag indicating if default options for |
The process is split into 4 steps:
First the two matrices are split according to the chromosomes.
We then compute correlations among the CpGs and compute CpG correlation blocks.
In each of the CpG correlation blocks, linear models according to the linear.model.type
qtlSetOption
with the CpG methylation state of the reference CpG specified by
representative.cpg.computation
as output and the SNP genotype state and all possible covariates
as input are computed.
For each of the CpG correlation blocks, we report the p-value of the representative CpG.
Currently, if qtlGetOption('cluster.architecture')=='sge'
the function does not return
a MethQTLResult
object, but NULL
, since monitoring finished jobs is hard
through SLURM. After the jobs are finished (checked using squeue
), the results can
can be loaded from out.dir
using loadMethQTLResult
.
An object of type MethQTLResult-class
containing the called methQTL interactions.
Michael Scherer
doMethQTLChromosome
meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
meth.qtl.res <- doMethQTL(meth.qtl,p.val.cutoff=0.01)
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