predictMeth {BiSeq} | R Documentation |
Uses local regression to predict methylation levels per sample.
predictMeth(object, h, grid.dist, mc.cores)
object |
A |
h |
Bandwidth in base pairs. Large values produce a smoother curve. Default is 80. |
grid.dist |
OPTIONAL. If |
mc.cores |
Passed to |
Uses binomLikelihoodSmooth
with pos
= CpG position, m
= number
methylated reads and n
= number of reads. pred.pos
corresponds to all CpG positions, or to the grid sites respectively, within the CpG clusters.
A BSrel
object containing the predicted methylation levels in
the methLevel
slot.
Katja Hebestreit
clusterSites
, binomLikelihoodSmooth
, mclapply
data(rrbs) rrbs.clust.unlim <- clusterSites(object = rrbs, groups = colData(rrbs)$group, perc.samples = 4/5, min.sites = 20, max.dist = 100) ind.cov <- totalReads(rrbs.clust.unlim) > 0 quant <- quantile(totalReads(rrbs.clust.unlim)[ind.cov], 0.9) rrbs.clust.lim <- limitCov(rrbs.clust.unlim, maxCov = quant) # with a small subset to save calculation time: rrbs.part <- rrbs.clust.lim[1:100,] predictedMeth <- predictMeth(object=rrbs.part)