Description Usage Arguments Value Details References See Also Examples
The function calculates differential methylation statistics between two groups of samples. The function uses either logistic regression test or Fisher's Exact test to calculate differential methylation. See references for detailed explanation on statistics.
1 | calculateDiffMeth(.Object,slim=TRUE,weigthed.mean=TRUE,num.cores=1)
|
.Object |
a methylBase object to calculate differential methylation |
slim |
If TRUE(default) SLIM method will be used for
P-value adjustment. If FALSE, |
weigthed.mean |
calculate the mean methylation difference between groups using read coverage as weights |
num.cores |
integer for denoting how many cores should be used for differential methylation calculations (only can be used in machines with multiple cores) |
a methylDiff object containing the differential methylation statistics and locations
The function either uses a logistic regression (when there are multiple samples per group) or fisher's exact when there is one sample per group.
Altuna Akalin, Matthias Kormaksson, Sheng Li, Francine E. Garrett-Bakelman, Maria E. Figueroa, Ari Melnick, Christopher E. Mason. (2012). "methylKit: A comprehensive R package for the analysis of genome-wide DNA methylation profiles." Genome Biology.
1 2 3 4 5 6 7 8 9 10 11 12 13 | data(methylKit)
# Logistic regression test will be applied since there are multiple samples in each group
# in methylBase.obj object
my.diffMeth=calculateDiffMeth(methylBase.obj,slim=TRUE,weigthed.mean=TRUE,num.cores=1)
# pool samples in each group
pooled.methylBase=pool(methylBase.obj,sample.ids=c("test","control"))
# After applying pool() function, there is one sample in each group.
# Fisher's exact test will be applied for differential methylation
my.diffMeth2=calculateDiffMeth(pooled.methylBase,slim=TRUE,
weigthed.mean=TRUE,num.cores=1)
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