View source: R/getLogitFracMeth.R
| getLogitFracMeth | R Documentation | 
Want an object with nominally Gaussian error for compartment inference, so this function uses 'suitable' (defaults to to 3 or more reads in 2 or more samples) measurements. Using Dirichlet smoothing (adding 'k' reads to M and U), these measurements are then turned into lightly moderated, logit-transformed methylated-fraction estimates for compartment calling.
getLogitFracMeth(x, minCov = 3, minSamp = 2, k = 0.1, r = NULL)
getMvals(x, minCov = 3, minSamp = 2, k = 0.1, r = NULL)
x | 
 A bsseq object with methylated and total reads  | 
minCov | 
 Minimum read coverage for landmarking samples (DEFAULT: 3)  | 
minSamp | 
 Minimum landmark samples with at least minCov (DEFAULT: 2)  | 
k | 
 Pseudoreads for smoothing (DEFAULT: 0.1)  | 
r | 
 Regions to collapse over - if NULL, do it by CpG (DEFAULT: NULL)  | 
Smoothed logit(M / Cov) GRanges with coordinates as row names
getMvals(): Alias for getLogitFracMeth
  orig_bed <- system.file("extdata", "MCF7_Cunha_chr11p15.bed.gz",
                          package="biscuiteer")
  orig_vcf <- system.file("extdata", "MCF7_Cunha_header_only.vcf.gz",
                          package="biscuiteer")
  bisc <- readBiscuit(BEDfile = orig_bed, VCFfile = orig_vcf,
                      merged = FALSE)
  reg <- GRanges(seqnames = rep("chr11",5),
                 strand = rep("*",5),
                 ranges = IRanges(start = c(0,2.8e6,1.17e7,1.38e7,1.69e7),
                                  end= c(2.8e6,1.17e7,1.38e7,1.69e7,2.2e7))
                 )
  frac <- getLogitFracMeth(bisc, minSamp = 1, r = reg)
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